Image-to-Text
Transformers
PyTorch
TensorBoard
English
mplug_owl2
feature-extraction
image-quality-assessment
document-quality
mplug-owl2
vision-language
document-analysis
sharpness
blur-detection
IQA
custom_code
Instructions to use mapo80/DeQA-Doc-Sharpness with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mapo80/DeQA-Doc-Sharpness with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "image-to-text" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("image-to-text", model="mapo80/DeQA-Doc-Sharpness", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("mapo80/DeQA-Doc-Sharpness", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
File size: 936 Bytes
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"add_bos_token": true,
"add_eos_token": false,
"added_tokens_decoder": {
"0": {
"content": "<unk>",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false,
"special": true
},
"1": {
"content": "<s>",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false,
"special": true
},
"2": {
"content": "</s>",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false,
"special": true
}
},
"bos_token": "<s>",
"clean_up_tokenization_spaces": false,
"eos_token": "</s>",
"legacy": false,
"model_max_length": 2048,
"pad_token": "<unk>",
"padding_side": "right",
"sp_model_kwargs": {},
"spaces_between_special_tokens": false,
"tokenizer_class": "LlamaTokenizer",
"unk_token": "<unk>",
"use_default_system_prompt": false
}
|