Feature Extraction
Transformers
Safetensors
fast_esm3
biology
protein-language-model
esm3
multimodal-protein-model
custom_code
Instructions to use Synthyra/ESM3_small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Synthyra/ESM3_small with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Synthyra/ESM3_small", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Synthyra/ESM3_small", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
Upload config
Browse files- README.md +4 -4
- config.json +0 -1
README.md
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library_name: transformers
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tags:
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# FastPLMs ESM3 Small
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library_name: transformers
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tags:
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- biology
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- protein-language-model
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- esm3
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- multimodal-protein-model
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# FastPLMs ESM3 Small
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config.json
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"AutoModel": "modeling_esm3.FastESM3Model",
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"AutoModelForMaskedLM": "modeling_esm3.FastESM3Model"
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},
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"dtype": "float32",
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"hidden_size": 1536,
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"initializer_range": 0.02,
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"model_name": "esm3_sm_open_v1",
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"AutoModel": "modeling_esm3.FastESM3Model",
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"AutoModelForMaskedLM": "modeling_esm3.FastESM3Model"
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},
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"hidden_size": 1536,
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"initializer_range": 0.02,
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"model_name": "esm3_sm_open_v1",
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