Instructions to use Synthyra/ESMplusplus_large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Synthyra/ESMplusplus_large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Synthyra/ESMplusplus_large", trust_remote_code=True)# Load model directly from transformers import AutoModelForMaskedLM model = AutoModelForMaskedLM.from_pretrained("Synthyra/ESMplusplus_large", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
File size: 747 Bytes
d0455eb 8b7df9e d0455eb | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 | {
"architectures": [
"ESMplusplusForMaskedLM"
],
"attn_backend": "sdpa",
"auto_map": {
"AutoConfig": "modeling_esm_plusplus.ESMplusplusConfig",
"AutoModel": "modeling_esm_plusplus.ESMplusplusModel",
"AutoModelForMaskedLM": "modeling_esm_plusplus.ESMplusplusForMaskedLM",
"AutoModelForSequenceClassification": "modeling_esm_plusplus.ESMplusplusForSequenceClassification",
"AutoModelForTokenClassification": "modeling_esm_plusplus.ESMplusplusForTokenClassification"
},
"dropout": 0.0,
"hidden_size": 1152,
"initializer_range": 0.02,
"model_type": "ESMplusplus",
"num_attention_heads": 18,
"num_hidden_layers": 36,
"tie_word_embeddings": false,
"transformers_version": "4.57.6",
"vocab_size": 64
}
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