Transformers
Safetensors
English
esmfold2
biology
esm
protein
protein-structure-prediction
structure-prediction
protein-design
3d-structure
confidence-estimation
molecular-dynamics
custom_code
Instructions to use biohub/ESMFold2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use biohub/ESMFold2 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("biohub/ESMFold2", trust_remote_code=True) model = AutoModel.from_pretrained("biohub/ESMFold2", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Fix extra_special_tokens: [] -> {} for transformers 4.x
Browse files- tokenizer_config.json +1 -1
tokenizer_config.json
CHANGED
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@@ -4,7 +4,7 @@
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"chain_break_token": "|",
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"cls_token": "<cls>",
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"eos_token": "<eos>",
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-
"extra_special_tokens":
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"mask_token": "<mask>",
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"model_max_length": 1000000000000000019884624838656,
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"pad_token": "<pad>",
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"chain_break_token": "|",
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"cls_token": "<cls>",
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"eos_token": "<eos>",
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+
"extra_special_tokens": {},
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"mask_token": "<mask>",
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| 9 |
"model_max_length": 1000000000000000019884624838656,
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| 10 |
"pad_token": "<pad>",
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