Instructions to use InstaDeepAI/nucleotide-transformer-2.5b-multi-species with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use InstaDeepAI/nucleotide-transformer-2.5b-multi-species with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="InstaDeepAI/nucleotide-transformer-2.5b-multi-species")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("InstaDeepAI/nucleotide-transformer-2.5b-multi-species") model = AutoModelForMaskedLM.from_pretrained("InstaDeepAI/nucleotide-transformer-2.5b-multi-species") - Notebooks
- Google Colab
- Kaggle
File size: 707 Bytes
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"architectures": [
"EsmForMaskedLM"
],
"attention_probs_dropout_prob": 0.0,
"emb_layer_norm_before": false,
"esmfold_config": null,
"hidden_dropout_prob": 0.0,
"hidden_size": 2560,
"initializer_range": 0.02,
"intermediate_size": 10240,
"is_folding_model": false,
"layer_norm_eps": 1e-12,
"mask_token_id": 2,
"max_position_embeddings": 1002,
"model_type": "esm",
"num_attention_heads": 20,
"num_hidden_layers": 32,
"pad_token_id": 1,
"position_embedding_type": "absolute",
"tie_word_embeddings": false,
"token_dropout": true,
"torch_dtype": "float32",
"transformers_version": "4.29.0.dev0",
"use_cache": false,
"vocab_list": null,
"vocab_size": 4105
}
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