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Add NT v2 100m model for sequence conservation prediction
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{
"_name_or_path": "NT_v2_100m_conservation",
"add_bias_fnn": false,
"architectures": [
"EsmForSequenceClassification"
],
"attention_probs_dropout_prob": 0.0,
"auto_map": {
"AutoConfig": "esm_config.EsmConfig",
"AutoModel": "modeling_esm.EsmModel",
"AutoModelForMaskedLM": "modeling_esm.EsmForMaskedLM",
"AutoModelForSequenceClassification": "modeling_esm.EsmForSequenceClassification"
},
"emb_layer_norm_before": false,
"esmfold_config": null,
"hidden_dropout_prob": 0.0,
"hidden_size": 512,
"id2label": {
"0": "Not conserved",
"1": "Conserved"
},
"initializer_range": 0.02,
"intermediate_size": 2048,
"is_folding_model": false,
"label2id": {
"Not conserved": 0,
"Conserved": 1
},
"layer_norm_eps": 1e-12,
"mask_token_id": 2,
"max_position_embeddings": 2050,
"model_type": "esm",
"num_attention_heads": 16,
"num_hidden_layers": 22,
"pad_token_id": 1,
"position_embedding_type": "rotary",
"problem_type": "single_label_classification",
"tie_word_embeddings": false,
"token_dropout": false,
"torch_dtype": "float32",
"transformers_version": "4.39.1",
"use_cache": false,
"vocab_list": null,
"vocab_size": 4107
}