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
| { | |
| "_name_or_path": "facebook/esm2_t6_8M_UR50D", | |
| "architectures": [ | |
| "EsmForTokenClassification" | |
| ], | |
| "attention_probs_dropout_prob": 0.0, | |
| "classifier_dropout": null, | |
| "emb_layer_norm_before": false, | |
| "esmfold_config": null, | |
| "hidden_act": "gelu", | |
| "hidden_dropout_prob": 0.0, | |
| "hidden_size": 320, | |
| "id2label": { | |
| "0": "No binding site", | |
| "1": "Binding site" | |
| }, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 1280, | |
| "is_folding_model": false, | |
| "label2id": { | |
| "Binding site": 1, | |
| "No binding site": 0 | |
| }, | |
| "layer_norm_eps": 1e-05, | |
| "mask_token_id": 32, | |
| "max_position_embeddings": 1026, | |
| "model_type": "esm", | |
| "num_attention_heads": 20, | |
| "num_hidden_layers": 6, | |
| "pad_token_id": 1, | |
| "position_embedding_type": "rotary", | |
| "token_dropout": true, | |
| "torch_dtype": "float32", | |
| "transformers_version": "4.32.1", | |
| "use_cache": true, | |
| "vocab_list": null, | |
| "vocab_size": 33 | |
| } | |