Fill-Mask
Transformers
Safetensors
English
esmc
biology
esm
protein
protein-language-model
protein-embeddings
masked-language-modeling
transfer-learning
variant-effect-prediction
protein-engineering
Instructions to use Rocketknight1/ESMC-600M-temp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Rocketknight1/ESMC-600M-temp with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Rocketknight1/ESMC-600M-temp")# Load model directly from transformers import AutoModelForMaskedLM model = AutoModelForMaskedLM.from_pretrained("Rocketknight1/ESMC-600M-temp", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "backend": "tokenizers", | |
| "bos_token": "<cls>", | |
| "chain_break_token": "|", | |
| "cls_token": "<cls>", | |
| "eos_token": "<eos>", | |
| "extra_special_tokens": [], | |
| "mask_token": "<mask>", | |
| "model_max_length": 1000000000000000019884624838656, | |
| "pad_token": "<pad>", | |
| "tokenizer_class": "EsmcTokenizer", | |
| "unk_token": "<unk>" | |
| } | |