Instructions to use InstaDeepAI/nucleotide-transformer-v2-50m-multi-species with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use InstaDeepAI/nucleotide-transformer-v2-50m-multi-species with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="InstaDeepAI/nucleotide-transformer-v2-50m-multi-species", trust_remote_code=True)# Load model directly from transformers import AutoModelForMaskedLM model = AutoModelForMaskedLM.from_pretrained("InstaDeepAI/nucleotide-transformer-v2-50m-multi-species", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
File size: 1,064 Bytes
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"add_bias_fnn": false,
"architectures": [
"EsmForMaskedLM",
"EsmForTokenClassification",
"EsmForSequenceClassification"
],
"attention_probs_dropout_prob": 0.0,
"auto_map": {
"AutoConfig": "esm_config.EsmConfig",
"AutoModelForMaskedLM": "modeling_esm.EsmForMaskedLM",
"AutoModelForTokenClassification": "modeling_esm.EsmForTokenClassification",
"AutoModelForSequenceClassification": "modeling_esm.EsmForSequenceClassification"
},
"emb_layer_norm_before": false,
"esmfold_config": null,
"hidden_dropout_prob": 0.0,
"hidden_size": 512,
"initializer_range": 0.02,
"intermediate_size": 2048,
"is_folding_model": false,
"layer_norm_eps": 1e-12,
"mask_token_id": 2,
"max_position_embeddings": 2050,
"num_attention_heads": 16,
"num_hidden_layers": 12,
"pad_token_id": 1,
"position_embedding_type": "rotary",
"tie_word_embeddings": false,
"token_dropout": false,
"torch_dtype": "float32",
"transformers_version": "4.32.0.dev0",
"use_cache": false,
"vocab_list": null,
"vocab_size": 4107
}
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