modelId stringlengths 4 81 | tags list | pipeline_tag stringclasses 17
values | config dict | downloads int64 0 59.7M | first_commit timestamp[ns, tz=UTC] | card stringlengths 51 438k |
|---|---|---|---|---|---|---|
Bharathdamu/wav2vec2-large-xls-r-300m-hindi-colab | [
"pytorch",
"tensorboard",
"wav2vec2",
"automatic-speech-recognition",
"dataset:common_voice",
"transformers",
"generated_from_trainer",
"license:apache-2.0"
] | automatic-speech-recognition | {
"architectures": [
"Wav2Vec2ForCTC"
],
"model_type": "wav2vec2",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_s... | 4 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- common_voice
model-index:
- name: wav2vec2-large-xls-r-300m-hindi-colab
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then ... |
Bharathdamu/wav2vec2-large-xls-r-300m-hindi | [
"pytorch",
"tensorboard",
"wav2vec2",
"automatic-speech-recognition",
"dataset:common_voice",
"transformers",
"generated_from_trainer",
"license:apache-2.0"
] | automatic-speech-recognition | {
"architectures": [
"Wav2Vec2ForCTC"
],
"model_type": "wav2vec2",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_s... | 10 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- common_voice
model-index:
- name: wav2vec2-large-xls-r-300m-hindi
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove... |
Bhuvana/t5-base-spellchecker | [
"pytorch",
"t5",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"T5ForConditionalGeneration"
],
"model_type": "t5",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": true,
"length_penalty": 2,
"max_length": 200,
"min_length": 30,
"no_repeat_ngram_s... | 93 | null | ---
widget:
- text: "christmas is celbrated on decembr 25 evry ear"
---
# Spell checker using T5 base transformer
A simple spell checker built using T5-Base transformer. To use this model
```
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
tokenizer = AutoTokenizer.from_pretrained("Bhuvana/t5-base-s... |
BigSalmon/GPTNeo350MInformalToFormalLincoln2 | [
"pytorch",
"gpt_neo",
"text-generation",
"transformers",
"has_space"
] | text-generation | {
"architectures": [
"GPTNeoForCausalLM"
],
"model_type": "gpt_neo",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram... | 8 | null | Trained on this model: https://huggingface.co/xhyi/PT_GPTNEO350_ATG/tree/main
```
How To Make Prompt:
informal english: i am very ready to do that just that.
Translated into the Style of Abraham Lincoln: you can assure yourself of my readiness to work toward this end.
Translated into the Style of Abraham Lincoln: plea... |
BigSalmon/GPTNeo350MInformalToFormalLincoln3 | [
"pytorch",
"gpt_neo",
"text-generation",
"transformers",
"has_space"
] | text-generation | {
"architectures": [
"GPTNeoForCausalLM"
],
"model_type": "gpt_neo",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram... | 10 | null | Trained on this model: https://huggingface.co/xhyi/PT_GPTNEO350_ATG/tree/main
```
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("BigSalmon/GPTNeo350MInformalToFormalLincoln3")
model = AutoModelForCausalLM.from_pretrained("BigSalmon/GPTNeo350MInformalToFormalLi... |
BigSalmon/GPTNeo350MInformalToFormalLincoln4 | [
"pytorch",
"gpt_neo",
"text-generation",
"transformers",
"has_space"
] | text-generation | {
"architectures": [
"GPTNeoForCausalLM"
],
"model_type": "gpt_neo",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram... | 11 | null | Trained on this model: https://huggingface.co/xhyi/PT_GPTNEO350_ATG/tree/main
```
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("BigSalmon/GPTNeo350MInformalToFormalLincoln3")
model = AutoModelForCausalLM.from_pretrained("BigSalmon/GPTNeo350MInformalToFormalLi... |
BigSalmon/GPTNeo350MInformalToFormalLincoln5 | [
"pytorch",
"gpt_neo",
"text-generation",
"transformers",
"has_space"
] | text-generation | {
"architectures": [
"GPTNeoForCausalLM"
],
"model_type": "gpt_neo",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram... | 11 | null | Trained on this model: https://huggingface.co/xhyi/PT_GPTNEO350_ATG/tree/main
```
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("BigSalmon/GPTNeo350MInformalToFormalLincoln3")
model = AutoModelForCausalLM.from_pretrained("BigSalmon/GPTNeo350MInformalToFormalLi... |
BigSalmon/InformalToFormalLincoln20 | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 8 | null | Informal to Formal:
Wordy to Concise:
Fill Missing Phrase:
```
from transformers import AutoTokenizer, AutoModelWithLMHead
tokenizer = AutoTokenizer.from_pretrained("BigSalmon/InformalToFormalLincoln20")
model = AutoModelWithLMHead.from_pretrained("BigSalmon/InformalToFormalLincoln20")
```
```
https://huggingface.c... |
BigSalmon/InformalToFormalLincoln21 | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"has_space"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 8 | null | Informal to Formal:
Wordy to Concise:
Fill Missing Phrase:
```
from transformers import AutoTokenizer, AutoModelWithLMHead
tokenizer = AutoTokenizer.from_pretrained("BigSalmon/InformalToFormalLincoln21")
model = AutoModelWithLMHead.from_pretrained("BigSalmon/InformalToFormalLincoln21")
```
```
https://huggingface.c... |
BigSalmon/InformalToFormalLincoln22 | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 6 | null | ```
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("BigSalmon/InformalToFormalLincoln22")
model = AutoModelForCausalLM.from_pretrained("BigSalmon/InformalToFormalLincoln22")
```
```
How To Make Prompt:
informal english: i am very ready to do that just that.
Tr... |
BigSalmon/InformalToFormalLincoln24 | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"has_space"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 5 | null | ```
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("BigSalmon/InformalToFormalLincoln24")
model = AutoModelForCausalLM.from_pretrained("BigSalmon/InformalToFormalLincoln24")
```
```
How To Make Prompt:
informal english: i am very ready to do that just that.
Tr... |
BigSalmon/InformalToFormalLincoln25 | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"has_space"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 10 | null | ```
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("BigSalmon/InformalToFormalLincoln25")
model = AutoModelForCausalLM.from_pretrained("BigSalmon/InformalToFormalLincoln25")
```
```
How To Make Prompt:
informal english: i am very ready to do that just that.
Tr... |
BigSalmon/MrLincoln11 | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 9 | null | Informal to Formal:
```
from transformers import AutoTokenizer, AutoModelWithLMHead
tokenizer = AutoTokenizer.from_pretrained("gpt2")
model = AutoModelWithLMHead.from_pretrained("BigSalmon/MrLincoln11")
```
```
How To Make Prompt:
Original: freedom of the press is a check against political corruption.
Edited: funda... |
BigSalmon/MrLincoln12 | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"has_space"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 9 | null | Informal to Formal:
```
from transformers import AutoTokenizer, AutoModelWithLMHead
tokenizer = AutoTokenizer.from_pretrained("gpt2")
model = AutoModelWithLMHead.from_pretrained("BigSalmon/MrLincoln12")
```
```
https://huggingface.co/spaces/BigSalmon/InformalToFormal
```
```
How To Make Prompt:
informal english: i... |
BigSalmon/MrLincoln7 | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | Informal to Formal:
```
from transformers import AutoTokenizer, AutoModelWithLMHead
tokenizer = AutoTokenizer.from_pretrained("gpt2")
model = AutoModelWithLMHead.from_pretrained("BigSalmon/MrLincoln7")
```
```
How To Make Prompt:
informal english: i am very ready to do that just that.
Translated into the Style ... |
BigSalmon/MrLincoln8 | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 12 | null | Informal to Formal:
```
from transformers import AutoTokenizer, AutoModelWithLMHead
tokenizer = AutoTokenizer.from_pretrained("gpt2")
model = AutoModelWithLMHead.from_pretrained("BigSalmon/MrLincoln7")
```
```
How To Make Prompt:
informal english: i am very ready to do that just that.
Translated into the Style ... |
BigSalmon/MrLincolnBerta | [
"pytorch",
"roberta",
"fill-mask",
"transformers",
"autotrain_compatible",
"has_space"
] | fill-mask | {
"architectures": [
"RobertaForMaskedLM"
],
"model_type": "roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngra... | 8 | null | Example Prompt:
```
informal english: things are better when they are open source, because they are constantly being updated to enhance experience.
Translated into the Style of Abraham Lincoln: in the open-source paradigm, code is ( ceaselessly / perpetually ) being ( reengineered / revamped / polished ), thereby ( adv... |
BigTooth/DialoGPT-small-tohru | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
"conversational": {
"max_length": 1000
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 10 | null | ---
tags:
- conversational
---
# Tohru DialoGPT model |
BigTooth/Megumin-v0.2 | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
"conversational": {
"max_length": 1000
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 13 | null | ---
tags:
- conversational
---
# Megumin-v0.2 model |
BigeS/DialoGPT-small-Rick | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
"conversational": {
"max_length": 1000
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 10 | null | ---
tags:
- conversational
---
#Rick Sanchez DialoGPT Model |
Blaine-Mason/hackMIT-finetuned-sst2 | [
"pytorch",
"tensorboard",
"bert",
"text-classification",
"dataset:glue",
"transformers",
"generated_from_trainer"
] | text-classification | {
"architectures": [
"BertForSequenceClassification"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_rep... | 36 | null | ---
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model_index:
- name: hackMIT-finetuned-sst2
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: glue
type: glue
args: sst2
metric:
name: Accuracy
type: accuracy
... |
Broadus20/DialoGPT-small-joshua | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
"conversational": {
"max_length": 1000
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 12 | null | ---
tags:
conversational
---
#Harry Potter DialoGPT Model |
Brykee/DialoGPT-medium-Morty | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
"conversational": {
"max_length": 1000
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 10 | null | ---
tags:
- conversational
---
# Morty DialoGPT Model |
CAMeL-Lab/bert-base-arabic-camelbert-ca-ner | [
"pytorch",
"tf",
"bert",
"token-classification",
"ar",
"arxiv:2103.06678",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | token-classification | {
"architectures": [
"BertForTokenClassification"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat... | 85 | null | ---
language:
- ar
license: apache-2.0
widget:
- text: "إمارة أبوظبي هي إحدى إمارات دولة الإمارات العربية المتحدة السبع"
---
# CAMeLBERT-CA NER Model
## Model description
**CAMeLBERT-CA NER Model** is a Named Entity Recognition (NER) model that was built by fine-tuning the [CAMeLBERT Classical Arabic (CA)](https://hu... |
CAMeL-Lab/bert-base-arabic-camelbert-ca-pos-egy | [
"pytorch",
"tf",
"bert",
"token-classification",
"ar",
"arxiv:2103.06678",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | token-classification | {
"architectures": [
"BertForTokenClassification"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat... | 16,451 | null | ---
language:
- ar
license: apache-2.0
widget:
- text: 'عامل ايه ؟'
---
# CAMeLBERT-CA POS-EGY Model
## Model description
**CAMeLBERT-CA POS-EGY Model** is a Egyptian Arabic POS tagging model that was built by fine-tuning the [CAMeLBERT-CA](https://huggingface.co/CAMeL-Lab/bert-base-arabic-camelbert-ca/) model.
For t... |
CAMeL-Lab/bert-base-arabic-camelbert-ca-pos-glf | [
"pytorch",
"tf",
"bert",
"token-classification",
"ar",
"arxiv:2103.06678",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | token-classification | {
"architectures": [
"BertForTokenClassification"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat... | 18 | null | ---
language:
- ar
license: apache-2.0
widget:
- text: 'شلونك ؟ شخبارك ؟'
---
# CAMeLBERT-CA POS-GLF Model
## Model description
**CAMeLBERT-CA POS-GLF Model** is a Gulf Arabic POS tagging model that was built by fine-tuning the [CAMeLBERT-CA](https://huggingface.co/CAMeL-Lab/bert-base-arabic-camelbert-ca/) model.
For... |
CAMeL-Lab/bert-base-arabic-camelbert-ca-pos-msa | [
"pytorch",
"tf",
"bert",
"token-classification",
"ar",
"arxiv:2103.06678",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | token-classification | {
"architectures": [
"BertForTokenClassification"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat... | 71 | null | ---
language:
- ar
license: apache-2.0
widget:
- text: 'إمارة أبوظبي هي إحدى إمارات دولة الإمارات العربية المتحدة السبع'
---
# CAMeLBERT-CA POS-MSA Model
## Model description
**CAMeLBERT-CA POS-MSA Model** is a Modern Standard Arabic (MSA) POS tagging model that was built by fine-tuning the [CAMeLBERT-CA](https://hug... |
CAMeL-Lab/bert-base-arabic-camelbert-ca-sentiment | [
"pytorch",
"tf",
"bert",
"text-classification",
"ar",
"arxiv:2103.06678",
"transformers",
"license:apache-2.0"
] | text-classification | {
"architectures": [
"BertForSequenceClassification"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_rep... | 73 | null | ---
language:
- ar
license: apache-2.0
widget:
- text: "أنا بخير"
---
# CAMeLBERT-CA SA Model
## Model description
**CAMeLBERT-CA SA Model** is a Sentiment Analysis (SA) model that was built by fine-tuning the [CAMeLBERT Classical Arabic (CA)](https://huggingface.co/CAMeL-Lab/bert-base-arabic-camelbert-ca/) model.
Fo... |
CAMeL-Lab/bert-base-arabic-camelbert-ca | [
"pytorch",
"tf",
"jax",
"bert",
"fill-mask",
"ar",
"arxiv:2103.06678",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"BertForMaskedLM"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 580 | null | ---
language:
- ar
license: apache-2.0
widget:
- text: "الهدف من الحياة هو [MASK] ."
---
# CAMeLBERT: A collection of pre-trained models for Arabic NLP tasks
## Model description
**CAMeLBERT** is a collection of BERT models pre-trained on Arabic texts with different sizes and variants.
We release pre-trained langu... |
CAMeL-Lab/bert-base-arabic-camelbert-da-ner | [
"pytorch",
"tf",
"bert",
"token-classification",
"ar",
"arxiv:2103.06678",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | token-classification | {
"architectures": [
"BertForTokenClassification"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat... | 42 | null | ---
language:
- ar
license: apache-2.0
widget:
- text: "إمارة أبوظبي هي إحدى إمارات دولة الإمارات العربية المتحدة السبع"
---
# CAMeLBERT-DA NER Model
## Model description
**CAMeLBERT-DA NER Model** is a Named Entity Recognition (NER) model that was built by fine-tuning the [CAMeLBERT Dialectal Arabic (DA)](https://hu... |
CAMeL-Lab/bert-base-arabic-camelbert-da-poetry | [
"pytorch",
"tf",
"bert",
"text-classification",
"ar",
"arxiv:1905.05700",
"arxiv:2103.06678",
"transformers",
"license:apache-2.0"
] | text-classification | {
"architectures": [
"BertForSequenceClassification"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_rep... | 37 | null | ---
language:
- ar
license: apache-2.0
widget:
- text: 'الخيل والليل والبيداء تعرفني [SEP] والسيف والرمح والقرطاس والقلم'
---
# CAMeLBERT-DA Poetry Classification Model
## Model description
**CAMeLBERT-DA Poetry Classification Model** is a poetry classification model that was built by fine-tuning the [CAMeLBERT Diale... |
CAMeL-Lab/bert-base-arabic-camelbert-da-pos-egy | [
"pytorch",
"tf",
"bert",
"token-classification",
"ar",
"arxiv:2103.06678",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | token-classification | {
"architectures": [
"BertForTokenClassification"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat... | 32 | null | ---
language:
- ar
license: apache-2.0
widget:
- text: 'عامل ايه ؟'
---
# CAMeLBERT-DA POS-EGY Model
## Model description
**CAMeLBERT-DA POS-EGY Model** is a Egyptian Arabic POS tagging model that was built by fine-tuning the [CAMeLBERT-DA](https://huggingface.co/CAMeL-Lab/bert-base-arabic-camelbert-da/) model.
For t... |
CAMeL-Lab/bert-base-arabic-camelbert-da-pos-glf | [
"pytorch",
"tf",
"bert",
"token-classification",
"ar",
"arxiv:2103.06678",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | token-classification | {
"architectures": [
"BertForTokenClassification"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat... | 54 | 2021-10-18T05:53:49Z | ---
language:
- ar
license: apache-2.0
widget:
- text: 'شلونك ؟ شخبارك ؟'
---
# CAMeLBERT-DA POS-GLF Model
## Model description
**CAMeLBERT-DA POS-GLF Model** is a Gulf Arabic POS tagging model that was built by fine-tuning the [CAMeLBERT-DA](https://huggingface.co/CAMeL-Lab/bert-base-arabic-camelbert-da/) model.
For... |
CAMeL-Lab/bert-base-arabic-camelbert-da-pos-msa | [
"pytorch",
"tf",
"bert",
"token-classification",
"ar",
"arxiv:2103.06678",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | token-classification | {
"architectures": [
"BertForTokenClassification"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat... | 27 | null | ---
language:
- ar
license: apache-2.0
widget:
- text: 'إمارة أبوظبي هي إحدى إمارات دولة الإمارات العربية المتحدة السبع'
---
# CAMeLBERT-DA POS-MSA Model
## Model description
**CAMeLBERT-DA POS-MSA Model** is a Modern Standard Arabic (MSA) POS tagging model that was built by fine-tuning the [CAMeLBERT-DA](https://hug... |
CAMeL-Lab/bert-base-arabic-camelbert-da-sentiment | [
"pytorch",
"tf",
"bert",
"text-classification",
"ar",
"arxiv:2103.06678",
"transformers",
"license:apache-2.0",
"has_space"
] | text-classification | {
"architectures": [
"BertForSequenceClassification"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_rep... | 19,850 | null | ---
language:
- ar
license: apache-2.0
widget:
- text: "أنا بخير"
---
# CAMeLBERT-DA SA Model
## Model description
**CAMeLBERT-DA SA Model** is a Sentiment Analysis (SA) model that was built by fine-tuning the [CAMeLBERT Dialectal Arabic (DA)](https://huggingface.co/CAMeL-Lab/bert-base-arabic-camelbert-da/) model.
Fo... |
CAMeL-Lab/bert-base-arabic-camelbert-da | [
"pytorch",
"tf",
"jax",
"bert",
"fill-mask",
"ar",
"arxiv:2103.06678",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"BertForMaskedLM"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 449 | null | ---
language:
- ar
license: apache-2.0
widget:
- text: "الهدف من الحياة هو [MASK] ."
---
# CAMeLBERT: A collection of pre-trained models for Arabic NLP tasks
## Model description
**CAMeLBERT** is a collection of BERT models pre-trained on Arabic texts with different sizes and variants.
We release pre-trained langu... |
CAMeL-Lab/bert-base-arabic-camelbert-mix-did-madar-corpus26 | [
"pytorch",
"tf",
"bert",
"text-classification",
"ar",
"arxiv:2103.06678",
"transformers",
"license:apache-2.0"
] | text-classification | {
"architectures": [
"BertForSequenceClassification"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_rep... | 45 | null | ---
language:
- ar
license: apache-2.0
widget:
- text: "عامل ايه ؟"
---
# CAMeLBERT-Mix DID Madar Corpus26 Model
## Model description
**CAMeLBERT-Mix DID Madar Corpus26 Model** is a dialect identification (DID) model that was built by fine-tuning the [CAMeLBERT-Mix](https://huggingface.co/CAMeL-Lab/bert-base-arabic-c... |
CAMeL-Lab/bert-base-arabic-camelbert-mix-did-madar-corpus6 | [
"pytorch",
"tf",
"bert",
"text-classification",
"ar",
"arxiv:2103.06678",
"transformers",
"license:apache-2.0"
] | text-classification | {
"architectures": [
"BertForSequenceClassification"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_rep... | 34 | null | ---
language:
- ar
license: apache-2.0
widget:
- text: "عامل ايه ؟"
---
# CAMeLBERT-Mix DID MADAR Corpus6 Model
## Model description
**CAMeLBERT-Mix DID MADAR Corpus6 Model** is a dialect identification (DID) model that was built by fine-tuning the [CAMeLBERT-Mix](https://huggingface.co/CAMeL-Lab/bert-base-arabic-cam... |
CAMeL-Lab/bert-base-arabic-camelbert-mix-did-nadi | [
"pytorch",
"tf",
"bert",
"text-classification",
"ar",
"arxiv:2103.06678",
"transformers",
"license:apache-2.0"
] | text-classification | {
"architectures": [
"BertForSequenceClassification"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_rep... | 63 | null | ---
language:
- ar
license: apache-2.0
widget:
- text: "عامل ايه ؟"
---
# CAMeLBERT-Mix DID NADI Model
## Model description
**CAMeLBERT-Mix DID NADI Model** is a dialect identification (DID) model that was built by fine-tuning the [CAMeLBERT-Mix](https://huggingface.co/CAMeL-Lab/bert-base-arabic-camelbert-mix/) model... |
CAMeL-Lab/bert-base-arabic-camelbert-mix-ner | [
"pytorch",
"tf",
"bert",
"token-classification",
"ar",
"arxiv:2103.06678",
"transformers",
"license:apache-2.0",
"autotrain_compatible",
"has_space"
] | token-classification | {
"architectures": [
"BertForTokenClassification"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat... | 1,860 | null | ---
language:
- ar
license: apache-2.0
widget:
- text: "إمارة أبوظبي هي إحدى إمارات دولة الإمارات العربية المتحدة السبع"
---
# CAMeLBERT-Mix NER Model
## Model description
**CAMeLBERT-Mix NER Model** is a Named Entity Recognition (NER) model that was built by fine-tuning the [CAMeLBERT Mix](https://huggingface.co/CAM... |
CAMeL-Lab/bert-base-arabic-camelbert-mix-poetry | [
"pytorch",
"tf",
"bert",
"text-classification",
"ar",
"arxiv:1905.05700",
"arxiv:2103.06678",
"transformers",
"license:apache-2.0"
] | text-classification | {
"architectures": [
"BertForSequenceClassification"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_rep... | 31 | null | ---
language:
- ar
license: apache-2.0
widget:
- text: 'الخيل والليل والبيداء تعرفني [SEP] والسيف والرمح والقرطاس والقلم'
---
# CAMeLBERT-Mix Poetry Classification Model
## Model description
**CAMeLBERT-Mix Poetry Classification Model** is a poetry classification model that was built by fine-tuning the [CAMeLBERT Mix... |
CAMeL-Lab/bert-base-arabic-camelbert-mix-pos-egy | [
"pytorch",
"tf",
"bert",
"token-classification",
"ar",
"arxiv:2103.06678",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | token-classification | {
"architectures": [
"BertForTokenClassification"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat... | 62 | null | ---
language:
- ar
license: apache-2.0
widget:
- text: 'عامل ايه ؟'
---
# CAMeLBERT-Mix POS-EGY Model
## Model description
**CAMeLBERT-Mix POS-EGY Model** is a Egyptian Arabic POS tagging model that was built by fine-tuning the [CAMeLBERT-Mix](https://huggingface.co/CAMeL-Lab/bert-base-arabic-camelbert-mix/) model.
F... |
CAMeL-Lab/bert-base-arabic-camelbert-mix-pos-glf | [
"pytorch",
"tf",
"bert",
"token-classification",
"ar",
"arxiv:2103.06678",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | token-classification | {
"architectures": [
"BertForTokenClassification"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat... | 132 | null | ---
language:
- ar
license: apache-2.0
widget:
- text: 'شلونك ؟ شخبارك ؟'
---
# CAMeLBERT-Mix POS-GLF Model
## Model description
**CAMeLBERT-Mix POS-GLF Model** is a Gulf Arabic POS tagging model that was built by fine-tuning the [CAMeLBERT-Mix](https://huggingface.co/CAMeL-Lab/bert-base-arabic-camelbert-mix/) model.... |
CAMeL-Lab/bert-base-arabic-camelbert-mix-pos-msa | [
"pytorch",
"tf",
"bert",
"token-classification",
"ar",
"arxiv:2103.06678",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | token-classification | {
"architectures": [
"BertForTokenClassification"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat... | 1,862 | null | ---
language:
- ar
license: apache-2.0
widget:
- text: 'إمارة أبوظبي هي إحدى إمارات دولة الإمارات العربية المتحدة السبع'
---
# CAMeLBERT-Mix POS-MSA Model
## Model description
**CAMeLBERT-Mix POS-MSA Model** is a Modern Standard Arabic (MSA) POS tagging model that was built by fine-tuning the [CAMeLBERT-Mix](https://... |
CAMeL-Lab/bert-base-arabic-camelbert-mix-sentiment | [
"pytorch",
"tf",
"bert",
"text-classification",
"ar",
"arxiv:2103.06678",
"transformers",
"license:apache-2.0"
] | text-classification | {
"architectures": [
"BertForSequenceClassification"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_rep... | 855 | null | ---
language:
- ar
license: apache-2.0
widget:
- text: "أنا بخير"
---
# CAMeLBERT Mix SA Model
## Model description
**CAMeLBERT Mix SA Model** is a Sentiment Analysis (SA) model that was built by fine-tuning the [CAMeLBERT Mix](https://huggingface.co/CAMeL-Lab/bert-base-arabic-camelbert-mix/) model.
For the fine-tuni... |
CAMeL-Lab/bert-base-arabic-camelbert-mix | [
"pytorch",
"tf",
"jax",
"bert",
"fill-mask",
"ar",
"arxiv:2103.06678",
"transformers",
"Arabic",
"Dialect",
"Egyptian",
"Gulf",
"Levantine",
"Classical Arabic",
"MSA",
"Modern Standard Arabic",
"license:apache-2.0",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"BertForMaskedLM"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 20,880 | null | ---
language:
- ar
license: apache-2.0
tags:
- Arabic
- Dialect
- Egyptian
- Gulf
- Levantine
- Classical Arabic
- MSA
- Modern Standard Arabic
widget:
- text: "الهدف من الحياة هو [MASK] ."
---
# CAMeLBERT: A collection of pre-trained models for Arabic NLP tasks
## Model description
**CAMeLBERT** is a collection... |
CAMeL-Lab/bert-base-arabic-camelbert-msa-did-madar-twitter5 | [
"pytorch",
"tf",
"bert",
"text-classification",
"ar",
"arxiv:2103.06678",
"transformers",
"license:apache-2.0"
] | text-classification | {
"architectures": [
"BertForSequenceClassification"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_rep... | 75 | null | ---
language:
- ar
license: apache-2.0
widget:
- text: "عامل ايه ؟"
---
# CAMeLBERT-MSA DID MADAR Twitter-5 Model
## Model description
**CAMeLBERT-MSA DID MADAR Twitter-5 Model** is a dialect identification (DID) model that was built by fine-tuning the [CAMeLBERT-MSA](https://huggingface.co/CAMeL-Lab/bert-base-arabic... |
CAMeL-Lab/bert-base-arabic-camelbert-msa-did-nadi | [
"pytorch",
"tf",
"bert",
"text-classification",
"ar",
"arxiv:2103.06678",
"transformers",
"license:apache-2.0"
] | text-classification | {
"architectures": [
"BertForSequenceClassification"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_rep... | 71 | null | ---
language:
- ar
license: apache-2.0
widget:
- text: "عامل ايه ؟"
---
# CAMeLBERT-MSA DID NADI Model
## Model description
**CAMeLBERT-MSA DID NADI Model** is a dialect identification (DID) model that was built by fine-tuning the [CAMeLBERT Modern Standard Arabic (MSA)](https://huggingface.co/CAMeL-Lab/bert-base-ara... |
CAMeL-Lab/bert-base-arabic-camelbert-msa-eighth | [
"pytorch",
"tf",
"jax",
"bert",
"fill-mask",
"ar",
"arxiv:2103.06678",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"BertForMaskedLM"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 21 | null | ---
language:
- ar
license: apache-2.0
widget:
- text: "الهدف من الحياة هو [MASK] ."
---
# CAMeLBERT: A collection of pre-trained models for Arabic NLP tasks
## Model description
**CAMeLBERT** is a collection of BERT models pre-trained on Arabic texts with different sizes and variants.
We release pre-trained langu... |
CAMeL-Lab/bert-base-arabic-camelbert-msa-half | [
"pytorch",
"tf",
"jax",
"bert",
"fill-mask",
"ar",
"arxiv:2103.06678",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"BertForMaskedLM"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 16 | null | ---
language:
- ar
license: apache-2.0
widget:
- text: "الهدف من الحياة هو [MASK] ."
---
# CAMeLBERT: A collection of pre-trained models for Arabic NLP tasks
## Model description
**CAMeLBERT** is a collection of BERT models pre-trained on Arabic texts with different sizes and variants.
We release pre-trained langu... |
CAMeL-Lab/bert-base-arabic-camelbert-msa-ner | [
"pytorch",
"tf",
"bert",
"token-classification",
"ar",
"arxiv:2103.06678",
"transformers",
"license:apache-2.0",
"autotrain_compatible",
"has_space"
] | token-classification | {
"architectures": [
"BertForTokenClassification"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat... | 229 | null | ---
language:
- ar
license: apache-2.0
widget:
- text: "إمارة أبوظبي هي إحدى إمارات دولة الإمارات العربية المتحدة السبع"
---
# CAMeLBERT MSA NER Model
## Model description
**CAMeLBERT MSA NER Model** is a Named Entity Recognition (NER) model that was built by fine-tuning the [CAMeLBERT Modern Standard Arabic (MSA)](h... |
CAMeL-Lab/bert-base-arabic-camelbert-msa-poetry | [
"pytorch",
"tf",
"bert",
"text-classification",
"ar",
"arxiv:1905.05700",
"arxiv:2103.06678",
"transformers",
"license:apache-2.0"
] | text-classification | {
"architectures": [
"BertForSequenceClassification"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_rep... | 25 | null | ---
language:
- ar
license: apache-2.0
widget:
- text: 'الخيل والليل والبيداء تعرفني [SEP] والسيف والرمح والقرطاس والقلم'
---
# CAMeLBERT-MSA Poetry Classification Model
## Model description
**CAMeLBERT-MSA Poetry Classification Model** is a poetry classification model that was built by fine-tuning the [CAMeLBERT Mod... |
CAMeL-Lab/bert-base-arabic-camelbert-msa-pos-egy | [
"pytorch",
"tf",
"bert",
"token-classification",
"ar",
"arxiv:2103.06678",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | token-classification | {
"architectures": [
"BertForTokenClassification"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat... | 52 | null | ---
language:
- ar
license: apache-2.0
widget:
- text: 'عامل ايه ؟'
---
# CAMeLBERT-MSA POS-EGY Model
## Model description
**CAMeLBERT-MSA POS-EGY Model** is a Egyptian Arabic POS tagging model that was built by fine-tuning the [CAMeLBERT-MSA](https://huggingface.co/CAMeL-Lab/bert-base-arabic-camelbert-msa/) model.
F... |
CAMeL-Lab/bert-base-arabic-camelbert-msa-pos-glf | [
"pytorch",
"tf",
"bert",
"token-classification",
"ar",
"arxiv:2103.06678",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | token-classification | {
"architectures": [
"BertForTokenClassification"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat... | 21 | null | ---
language:
- ar
license: apache-2.0
widget:
- text: 'شلونك ؟ شخبارك ؟'
---
# CAMeLBERT-MSA POS-GLF Model
## Model description
**CAMeLBERT-MSA POS-GLF Model** is a Gulf Arabic POS tagging model that was built by fine-tuning the [CAMeLBERT-MSA](https://huggingface.co/CAMeL-Lab/bert-base-arabic-camelbert-msa/) model.... |
CAMeL-Lab/bert-base-arabic-camelbert-msa-pos-msa | [
"pytorch",
"tf",
"bert",
"token-classification",
"ar",
"arxiv:2103.06678",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | token-classification | {
"architectures": [
"BertForTokenClassification"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat... | 133 | null | ---
language:
- ar
license: apache-2.0
widget:
- text: 'إمارة أبوظبي هي إحدى إمارات دولة الإمارات العربية المتحدة السبع'
---
# CAMeLBERT-MSA POS-MSA Model
## Model description
**CAMeLBERT-MSA POS-MSA Model** is a Modern Standard Arabic (MSA) POS tagging model that was built by fine-tuning the [CAMeLBERT-MSA](https://... |
CAMeL-Lab/bert-base-arabic-camelbert-msa-quarter | [
"pytorch",
"tf",
"jax",
"bert",
"fill-mask",
"ar",
"arxiv:2103.06678",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"BertForMaskedLM"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 12 | null | ---
language:
- ar
license: apache-2.0
widget:
- text: "الهدف من الحياة هو [MASK] ."
---
# CAMeLBERT: A collection of pre-trained models for Arabic NLP tasks
## Model description
**CAMeLBERT** is a collection of BERT models pre-trained on Arabic texts with different sizes and variants.
We release pre-trained langu... |
CAMeL-Lab/bert-base-arabic-camelbert-msa-sentiment | [
"pytorch",
"tf",
"bert",
"text-classification",
"ar",
"arxiv:2103.06678",
"transformers",
"license:apache-2.0"
] | text-classification | {
"architectures": [
"BertForSequenceClassification"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_rep... | 574 | null | ---
language:
- ar
license: apache-2.0
widget:
- text: "أنا بخير"
---
# CAMeLBERT MSA SA Model
## Model description
**CAMeLBERT MSA SA Model** is a Sentiment Analysis (SA) model that was built by fine-tuning the [CAMeLBERT Modern Standard Arabic (MSA)](https://huggingface.co/CAMeL-Lab/bert-base-arabic-camelbert-msa/)... |
CAMeL-Lab/bert-base-arabic-camelbert-msa-sixteenth | [
"pytorch",
"tf",
"jax",
"bert",
"fill-mask",
"ar",
"arxiv:2103.06678",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"BertForMaskedLM"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 26 | null | ---
language:
- ar
license: apache-2.0
widget:
- text: "الهدف من الحياة هو [MASK] ."
---
# CAMeLBERT: A collection of pre-trained models for Arabic NLP tasks
## Model description
**CAMeLBERT** is a collection of BERT models pre-trained on Arabic texts with different sizes and variants.
We release pre-trained langu... |
CAMeL-Lab/bert-base-arabic-camelbert-msa | [
"pytorch",
"tf",
"jax",
"bert",
"fill-mask",
"ar",
"arxiv:2103.06678",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"BertForMaskedLM"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 2,967 | 2021-03-11T11:20:49Z | ---
language:
- ar
license: apache-2.0
widget:
- text: "الهدف من الحياة هو [MASK] ."
---
# CAMeLBERT: A collection of pre-trained models for Arabic NLP tasks
## Model description
**CAMeLBERT** is a collection of BERT models pre-trained on Arabic texts with different sizes and variants.
We release pre-trained langu... |
CAUKiel/JavaBERT-uncased | [
"pytorch",
"safetensors",
"bert",
"fill-mask",
"java",
"code",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"BertForMaskedLM"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 7 | null | ---
language:
- java
- code
license: apache-2.0
widget:
- text: 'public [MASK] isOdd(Integer num){if (num % 2 == 0) {return "even";} else {return "odd";}}'
---
## JavaBERT
A BERT-like model pretrained on Java software code.
### Training Data
The model was trained on 2,998,345 Java files retrieved from open sourc... |
CAUKiel/JavaBERT | [
"pytorch",
"safetensors",
"bert",
"fill-mask",
"code",
"arxiv:2110.10404",
"arxiv:1910.09700",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"BertForMaskedLM"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 388 | null |
---
language:
- code
license: apache-2.0
widget:
- text: public [MASK] isOdd(Integer num) {if (num % 2 == 0) {return "even";} else
{return "odd";}}
---
# Model Card for JavaBERT
A BERT-like model pretrained on Java software code.
# Model Details
## Model Description
A BERT-like model pretrained ... |
CLAck/en-vi | [
"pytorch",
"marian",
"text2text-generation",
"en",
"vi",
"dataset:ALT",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | {
"architectures": [
"MarianMTModel"
],
"model_type": "marian",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 8 | 2022-02-12T17:04:02Z | ---
language:
- en
- vi
tags:
- translation
license: apache-2.0
datasets:
- ALT
metrics:
- sacrebleu
---
This is a finetuning of a MarianMT pretrained on English-Chinese. The target language pair is English-Vietnamese.
The first phase of training (mixed) is performed on a dataset containing both English-Chinese and En... |
CLAck/indo-pure | [
"pytorch",
"marian",
"text2text-generation",
"en",
"id",
"dataset:ALT",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | {
"architectures": [
"MarianMTModel"
],
"model_type": "marian",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 4 | 2022-02-02T09:13:34Z | ---
language:
- en
- id
tags:
- translation
license: apache-2.0
datasets:
- ALT
metrics:
- sacrebleu
---
Pure fine-tuning version of MarianMT en-zh on Indonesian Language
### Example
```
%%capture
!pip install transformers transformers[sentencepiece]
from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
# Dow... |
CLAck/vi-en | [
"pytorch",
"marian",
"text2text-generation",
"en",
"vi",
"dataset:ALT",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | {
"architectures": [
"MarianMTModel"
],
"model_type": "marian",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 6 | 2022-02-12T16:50:15Z | ---
language:
- en
- vi
tags:
- translation
license: apache-2.0
datasets:
- ALT
metrics:
- sacrebleu
---
This is a finetuning of a MarianMT pretrained on Chinese-English. The target language pair is Vietnamese-English.
### Example
```
%%capture
!pip install transformers transformers[sentencepiece]
from transformers ... |
CLTL/gm-ner-xlmrbase | [
"pytorch",
"tf",
"xlm-roberta",
"token-classification",
"nl",
"transformers",
"dighum",
"license:apache-2.0",
"autotrain_compatible"
] | token-classification | {
"architectures": [
"XLMRobertaForTokenClassification"
],
"model_type": "xlm-roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
... | 2 | 2021-10-27T11:16:42Z | ---
language: nl
license: apache-2.0
tags:
- dighum
pipeline_tag: token-classification
---
# Early-modern Dutch NER (General Letters)
## Description
This is a fine-tuned NER model for early-modern Dutch United East India Company (VOC) letters based on XLM-R_base [(Conneau et al., 2020)](https://aclanthology.org/2020.... |
CLTL/icf-domains | [
"pytorch",
"roberta",
"nl",
"transformers",
"license:mit",
"text-classification"
] | text-classification | {
"architectures": [
"RobertaForMultiLabelSequenceClassification"
],
"model_type": "roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": nul... | 35 | null | ---
language: nl
license: mit
pipeline_tag: text-classification
inference: false
---
# A-PROOF ICF-domains Classification
## Description
A fine-tuned multi-label classification model that detects 9 [WHO-ICF](https://www.who.int/standards/classifications/international-classification-of-functioning-disability-and-heal... |
CLTL/icf-levels-att | [
"pytorch",
"roberta",
"text-classification",
"nl",
"transformers",
"license:mit"
] | text-classification | {
"architectures": [
"RobertaForSequenceClassification"
],
"model_type": "roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"... | 32 | null | ---
language: nl
license: mit
pipeline_tag: text-classification
inference: false
---
# Regression Model for Attention Functioning Levels (ICF b140)
## Description
A fine-tuned regression model that assigns a functioning level to Dutch sentences describing attention functions. The model is based on a pre-trained Dutch... |
CLTL/icf-levels-ber | [
"pytorch",
"roberta",
"text-classification",
"nl",
"transformers",
"license:mit"
] | text-classification | {
"architectures": [
"RobertaForSequenceClassification"
],
"model_type": "roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"... | 33 | 2021-10-06T12:23:03Z | ---
language: nl
license: mit
pipeline_tag: text-classification
inference: false
---
# Regression Model for Work and Employment Functioning Levels (ICF d840-d859)
## Description
A fine-tuned regression model that assigns a functioning level to Dutch sentences describing work and employment functions. The model is bas... |
CLTL/icf-levels-fac | [
"pytorch",
"roberta",
"text-classification",
"nl",
"transformers",
"license:mit"
] | text-classification | {
"architectures": [
"RobertaForSequenceClassification"
],
"model_type": "roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"... | 32 | 2021-10-06T12:23:36Z | ---
language: nl
license: mit
pipeline_tag: text-classification
inference: false
---
# Regression Model for Walking Functioning Levels (ICF d550)
## Description
A fine-tuned regression model that assigns a functioning level to Dutch sentences describing walking functions. The model is based on a pre-trained Dutch med... |
CLTL/icf-levels-mbw | [
"pytorch",
"roberta",
"text-classification",
"nl",
"transformers",
"license:mit"
] | text-classification | {
"architectures": [
"RobertaForSequenceClassification"
],
"model_type": "roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"... | 30 | null | ---
language: nl
license: mit
pipeline_tag: text-classification
inference: false
---
# Regression Model for Weight Maintenance Functioning Levels (ICF b530)
## Description
A fine-tuned regression model that assigns a functioning level to Dutch sentences describing weight maintenance functions. The model is based on a... |
Canadiancaleb/DialoGPT-small-jesse | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
"conversational": {
"max_length": 1000
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 9 | null | ---
tags:
- conversational
---
# Jesse (Breaking Bad) DialoGPT Model |
Captain-1337/CrudeBERT | [
"pytorch",
"bert",
"text-classification",
"arxiv:1908.10063",
"transformers"
] | text-classification | {
"architectures": [
"BertForSequenceClassification"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_rep... | 28 | null | # Master Thesis
## Predictive Value of Sentiment Analysis from Headlines for Crude Oil Prices
### Understanding and Exploiting Deep Learning-based Sentiment Analysis from News Headlines for Predicting Price Movements of WTI Crude Oil
The focus of this thesis deals with the task of research and development of state-of-... |
CarlosPR/mt5-spanish-memmories-analysis | [
"pytorch",
"mt5",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"MT5ForConditionalGeneration"
],
"model_type": "mt5",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat... | 7 | null | **mt5-spanish-memmories-analysis**
**// ES**
Este es un trabajo en proceso.
Este modelo aún es solo un punto de control inicial que mejoraré en los próximos meses.
El objetivo es proporcionar un modelo capaz de, utilizando una combinación de tareas del modelo mT5, comprender los recuerdos y proporcionar una interacc... |
CennetOguz/distilbert-base-uncased-finetuned-recipe | [
"pytorch",
"tensorboard",
"distilbert",
"fill-mask",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"DistilBertForMaskedLM"
],
"model_type": "distilbert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repea... | 2 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: distilbert-base-uncased-finetuned-recipe
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -... |
Chae/botman | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
"conversational": {
"max_length": 1000
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 5 | null | ---
tags:
- conversational
---
# Lego Batman DialoGPT Model |
Chakita/KannadaBERT | [
"pytorch",
"roberta",
"fill-mask",
"transformers",
"masked-lm",
"fill-in-the-blanks",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"RobertaForMaskedLM"
],
"model_type": "roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngra... | 5 | null | ---
tags:
- masked-lm
- fill-in-the-blanks
---
RoBERTa model trained on OSCAR Kannada corpus. |
ChristianOrr/madnet_keras | [
"tensorboard",
"dataset:flyingthings-3d",
"dataset:kitti",
"arxiv:1810.05424",
"vision",
"deep-stereo",
"depth-estimation",
"Tensorflow2",
"Keras",
"license:apache-2.0"
] | depth-estimation | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
license: apache-2.0
tags:
- vision
- deep-stereo
- depth-estimation
- Tensorflow2
- Keras
datasets:
- flyingthings-3d
- kitti
---
# MADNet Keras
MADNet is a deep stereo depth estimation model. Its key defining features are:
1. It has a light-weight architecture which means it has low latency.
2... |
ChristopherA08/IndoELECTRA | [
"pytorch",
"electra",
"pretraining",
"id",
"dataset:oscar",
"transformers"
] | null | {
"architectures": [
"ElectraForPreTraining"
],
"model_type": "electra",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_n... | 4 | null | ---
language: id
datasets:
- oscar
---
# IndoBERT (Indonesian BERT Model)
## Model description
ELECTRA is a new method for self-supervised language representation learning. This repository contains the pre-trained Electra Base model (tensorflow 1.15.0) trained in a Large Indonesian corpus (~16GB of raw text | ~2B indo... |
ChukSamuels/DialoGPT-small-Dr.FauciBot | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
"conversational": {
"max_length": 1000
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 13 | null | ---
tags:
- conversational
---
# Dr. Fauci DialoGPT Model |
Cinnamon/electra-small-japanese-discriminator | [
"pytorch",
"electra",
"pretraining",
"ja",
"transformers",
"license:apache-2.0"
] | null | {
"architectures": [
"ElectraForPreTraining"
],
"model_type": "electra",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_n... | 419 | null | ---
language: ja
license: apache-2.0
---
## Japanese ELECTRA-small
We provide a Japanese **ELECTRA-Small** model, as described in [ELECTRA: Pre-training Text Encoders as Discriminators Rather Than Generators](https://openreview.net/pdf?id=r1xMH1BtvB).
Our pretraining process employs subword units derived from the [J... |
Cinnamon/electra-small-japanese-generator | [
"pytorch",
"electra",
"fill-mask",
"ja",
"transformers",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"ElectraForMaskedLM"
],
"model_type": "electra",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngra... | 19 | null | ---
language: ja
---
## Japanese ELECTRA-small
We provide a Japanese **ELECTRA-Small** model, as described in [ELECTRA: Pre-training Text Encoders as Discriminators Rather Than Generators](https://openreview.net/pdf?id=r1xMH1BtvB).
Our pretraining process employs subword units derived from the [Japanese Wikipedia](ht... |
Ciruzzo/DialoGPT-small-harrypotter | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
"conversational": {
"max_length": 1000
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 9 | null | ---
tags:
- conversational
---
# Harry Potter DialoGPT Model |
ClaudeCOULOMBE/RickBot | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
"conversational": {
"max_length": 1000
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 9 | null | ---
tags:
- conversational
---
# RickBot built for [Chai](https://chai.ml/)
Make your own [here](https://colab.research.google.com/drive/1o5LxBspm-C28HQvXN-PRQavapDbm5WjG?usp=sharing)
|
ClaudeYang/awesome_fb_model | [
"pytorch",
"bart",
"text-classification",
"dataset:multi_nli",
"transformers",
"zero-shot-classification"
] | zero-shot-classification | {
"architectures": [
"BartForSequenceClassification"
],
"model_type": "bart",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_rep... | 26 | null | ---
pipeline_tag: zero-shot-classification
datasets:
- multi_nli
widget:
- text: "ETH"
candidate_labels: "Location & Address, Employment, Organizational, Name, Service, Studies, Science"
hypothesis_template: "This is {}."
---
ETH Zeroshot |
CogComp/bart-faithful-summary-detector | [
"pytorch",
"jax",
"bart",
"text-classification",
"en",
"dataset:xsum",
"transformers",
"xsum",
"license:cc-by-sa-4.0"
] | text-classification | {
"architectures": [
"BartForSequenceClassification"
],
"model_type": "bart",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": 1,
"max_length": 128,
"min_length": 12,
"no_repeat_ng... | 234 | null | ---
language:
- en
thumbnail: https://cogcomp.seas.upenn.edu/images/logo.png
tags:
- text-classification
- bart
- xsum
license: cc-by-sa-4.0
datasets:
- xsum
widget:
- text: "<s> Ban Ki-moon was elected for a second term in 2007. </s></s> Ban Ki-Moon was re-elected for a second term by the UN General Assembly, unoppos... |
Coolhand/Abuela | [
"en",
"image_restoration",
"superresolution",
"license:mit"
] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
language:
- en
thumbnail: https://github.com/Nick-Harvey/for_my_abuela/blob/master/cuban_large.jpg
tags:
- image_restoration
- superresolution
license: mit
metrics:
---
@inproceedings{wan2020bringing,
title={Bringing Old Photos Back to Life},
author={Wan, Ziyu and Zhang, Bo and Chen, Dongdong and Zhang, Pan and Ch... |
CopymySkill/DialoGPT-medium-atakan | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
"conversational": {
"max_length": 1000
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 7 | 2021-09-23T17:08:19Z | ---
tags:
- conversational
---
# Atakan DialoGPT Model |
Corvus/DialoGPT-medium-CaptainPrice-Extended | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
"conversational": {
"max_length": 1000
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 7 | null | ---
tags:
- conversational
---
#DiabloGPT Captain Price (Extended) |
Corvus/DialoGPT-medium-CaptainPrice | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
"conversational": {
"max_length": 1000
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 7 | null | ---
tags:
- conversational
---
# Captain Price DialoGPT Model |
CouchCat/ma_mlc_v7_distil | [
"pytorch",
"distilbert",
"text-classification",
"en",
"transformers",
"multi-label",
"license:mit"
] | text-classification | {
"architectures": [
"DistilBertForSequenceClassification"
],
"model_type": "distilbert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
... | 29 | 2021-02-14T11:20:32Z | ---
language: en
license: mit
tags:
- multi-label
widget:
- text: "I would like to return these pants and shoes"
---
### Description
A Multi-label text classification model trained on a customer feedback data using DistilBert.
Possible labels are:
- Delivery (delivery status, time of arrival, etc.)
- Return (return co... |
CouchCat/ma_ner_v6_distil | [
"pytorch",
"distilbert",
"token-classification",
"en",
"transformers",
"ner",
"license:mit",
"autotrain_compatible"
] | token-classification | {
"architectures": [
"DistilBertForTokenClassification"
],
"model_type": "distilbert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
... | 6 | 2021-02-14T11:34:25Z | ---
language: en
license: mit
tags:
- ner
widget:
- text: "These shoes from Adidas fit quite well"
---
### Description
A Named Entity Recognition model trained on a customer feedback data using DistilBert.
Possible labels are:
- PRD: for certain products
- BRND: for brands
### Usage
```
from transformers import AutoT... |
CouchCat/ma_ner_v7_distil | [
"pytorch",
"distilbert",
"token-classification",
"en",
"transformers",
"ner",
"license:mit",
"autotrain_compatible"
] | token-classification | {
"architectures": [
"DistilBertForTokenClassification"
],
"model_type": "distilbert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
... | 13 | null | ---
language: en
license: mit
tags:
- ner
widget:
- text: "These shoes I recently bought from Tommy Hilfiger fit quite well. The shirt, however, has got a hole"
---
### Description
A Named Entity Recognition model trained on a customer feedback data using DistilBert.
Possible labels are in BIO-notation. Performan... |
CouchCat/ma_sa_v7_distil | [
"pytorch",
"distilbert",
"text-classification",
"en",
"transformers",
"sentiment-analysis",
"license:mit"
] | text-classification | {
"architectures": [
"DistilBertForSequenceClassification"
],
"model_type": "distilbert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
... | 38 | 2021-02-12T17:16:43Z | ---
language: en
license: mit
tags:
- sentiment-analysis
widget:
- text: "I am disappointed in the terrible quality of my dress"
---
### Description
A Sentiment Analysis model trained on customer feedback data using DistilBert.
Possible sentiments are:
* negative
* neutral
* positive
### Usage
```
from transformers ... |
Cryptikdw/DialoGPT-small-rick | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
"conversational": {
"max_length": 1000
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 7 | null | ---
tags:
- conversational
---
#rick DialoGPT Model |
CuongLD/wav2vec2-large-xlsr-vietnamese | [
"pytorch",
"jax",
"wav2vec2",
"automatic-speech-recognition",
"vi",
"dataset:common_voice, infore_25h",
"arxiv:2006.11477",
"arxiv:2006.13979",
"transformers",
"audio",
"speech",
"xlsr-fine-tuning-week",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | {
"architectures": [
"Wav2Vec2ForCTC"
],
"model_type": "wav2vec2",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_s... | 8 | null | ---
language: vi
datasets:
- common_voice, infore_25h
metrics:
- wer
tags:
- audio
- automatic-speech-recognition
- speech
- xlsr-fine-tuning-week
license: apache-2.0
model-index:
- name: Cuong-Cong XLSR Wav2Vec2 Large 53
results:
- task:
name: Speech Recognition
type: automatic-speech-recognition
... |
CurtisBowser/DialoGPT-medium-sora-two | [
"pytorch",
"conversational"
] | conversational | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | 2021-11-04T03:17:16Z | ---
tags:
- conversational
---
# Sora DialoGPT Model |
CurtisBowser/DialoGPT-medium-sora | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
"conversational": {
"max_length": 1000
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 7 | 2021-10-20T23:52:19Z | ---
tags:
- conversational
---
# Sora DialoGPT Model
|
CurtisBowser/DialoGPT-small-sora | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
"conversational": {
"max_length": 1000
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 7 | 2021-10-20T20:22:23Z | ---
tags:
- conversational
---
# Sora DialoGPT Model |
CyberMuffin/DialoGPT-small-ChandlerBot | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
"conversational": {
"max_length": 1000
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 9 | null | ---
tags:
- conversational
---
# Chandler Bot DialoGPT model |
D3xter1922/electra-base-discriminator-finetuned-cola | [
"pytorch",
"tensorboard",
"electra",
"text-classification",
"dataset:glue",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | {
"architectures": [
"ElectraForSequenceClassification"
],
"model_type": "electra",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"... | 68 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- matthews_correlation
model-index:
- name: electra-base-discriminator-finetuned-cola
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: glue
type: glue
args: cola
... |
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