Instructions to use nvidia/esm2_t12_35M_UR50D with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nvidia/esm2_t12_35M_UR50D with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="nvidia/esm2_t12_35M_UR50D", trust_remote_code=True)# Load model directly from transformers import AutoModelForMaskedLM model = AutoModelForMaskedLM.from_pretrained("nvidia/esm2_t12_35M_UR50D", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "add_cross_attention": false, | |
| "add_pooling_layer": false, | |
| "architectures": [ | |
| "NVEsmForMaskedLM" | |
| ], | |
| "attention_probs_dropout_prob": 0.0, | |
| "attn_input_format": "bshd", | |
| "attn_mask_type": "padding", | |
| "auto_map": { | |
| "AutoConfig": "esm_nv.NVEsmConfig", | |
| "AutoModel": "esm_nv.NVEsmModel", | |
| "AutoModelForMaskedLM": "esm_nv.NVEsmForMaskedLM", | |
| "AutoModelForTokenClassification": "esm_nv.NVEsmForTokenClassification" | |
| }, | |
| "classifier_dropout": null, | |
| "dtype": "float32", | |
| "emb_layer_norm_before": false, | |
| "encoder_activation": "gelu", | |
| "esmfold_config": null, | |
| "fuse_qkv_params": true, | |
| "hidden_act": "gelu", | |
| "hidden_dropout_prob": 0.0, | |
| "hidden_size": 480, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 1920, | |
| "is_decoder": false, | |
| "is_folding_model": false, | |
| "layer_norm_eps": 1e-05, | |
| "layer_precision": null, | |
| "mask_token_id": 32, | |
| "max_position_embeddings": 1026, | |
| "max_seq_length": null, | |
| "micro_batch_size": null, | |
| "model_type": "nv_esm", | |
| "num_attention_heads": 20, | |
| "num_hidden_layers": 12, | |
| "pad_token_id": 1, | |
| "padded_vocab_size": 33, | |
| "position_embedding_type": "rotary", | |
| "qkv_weight_interleaved": true, | |
| "tie_word_embeddings": true, | |
| "token_dropout": true, | |
| "transformers_version": "5.5.0", | |
| "use_cache": true, | |
| "use_quantized_model_init": false, | |
| "vocab_list": null, | |
| "vocab_size": 33 | |
| } |