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, device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 1,346 Bytes
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"architectures": [
"ESMplusplusForMaskedLM"
],
"attn_backend": "sdpa",
"auto_map": {
"AutoConfig": "modeling_fastplms.ESMplusplusConfig",
"AutoModel": "modeling_fastplms.ESMplusplusModel",
"AutoModelForMaskedLM": "modeling_fastplms.ESMplusplusForMaskedLM"
},
"dropout": 0.0,
"fastplms_checkpoint_hash": "b69fa1f6ed3de70da4f851f70e4aed30f6dcc36137d023d8d72a718e5ce0dd94",
"fastplms_checkpoint_repo_id": "Synthyra/ESMplusplus_large",
"fastplms_checkpoint_revision": "f813401638b3fddab09748aec1ad2bf537aa4208",
"fastplms_model_id": "esmc_large",
"fastplms_release_tool_revision": "e6dd397a9ad368c998d714f6bd64d40b533d1ed1",
"fastplms_release_tool_sha256": "6d335c05aa49a232086a816deb25d248d1490529e5783acc3355b9bc6f03e0c2",
"fastplms_runtime_bundle_sha256": "d73f544a7623d12eff2ba407e2d7e86417b7d731e36a2931515930eae7d7e8e5",
"fastplms_runtime_revision": "e6dd397a9ad368c998d714f6bd64d40b533d1ed1",
"fastplms_source_tree_sha256": "bed9c7b1e1b0500dcd370e92e1f83b47494f9167d37b16e248f9d17e0135f822",
"fastplms_weights_revision": "f813401638b3fddab09748aec1ad2bf537aa4208",
"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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