Token Classification
Transformers
PyTorch
Safetensors
English
esm
biology
esm2
ESM-2
protein language model
Instructions to use AmelieSchreiber/esm2_t6_8M_general_binding_sites_v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AmelieSchreiber/esm2_t6_8M_general_binding_sites_v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="AmelieSchreiber/esm2_t6_8M_general_binding_sites_v2")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("AmelieSchreiber/esm2_t6_8M_general_binding_sites_v2") model = AutoModelForTokenClassification.from_pretrained("AmelieSchreiber/esm2_t6_8M_general_binding_sites_v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- edc55f833ccd4173dbc933dba71770ad65d17253f5deaa3f80eaf4aa251b9b40
- Size of remote file:
- 59.4 MB
- SHA256:
- 3b34d5c14b8b9e0c44a70543648cef9c2279dc4d85eb827f432d35cc23fb8e39
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