Fill-Mask
Transformers
Safetensors
English
bert
protein
protbert
masked-language-modeling
bioinformatics
sequence-prediction
Instructions to use faceless-void/protbert-sequence-unmasking with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use faceless-void/protbert-sequence-unmasking with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="faceless-void/protbert-sequence-unmasking")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("faceless-void/protbert-sequence-unmasking") model = AutoModelForMaskedLM.from_pretrained("faceless-void/protbert-sequence-unmasking") - Notebooks
- Google Colab
- Kaggle
| { | |
| "_from_model_config": true, | |
| "pad_token_id": 0, | |
| "transformers_version": "4.41.1" | |
| } | |