Instructions to use Synthyra/ESM2-650M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Synthyra/ESM2-650M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Synthyra/ESM2-650M", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForMaskedLM model = AutoModelForMaskedLM.from_pretrained("Synthyra/ESM2-650M", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
10 days ago
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Update FastPLMs files from Synthyra/FastPLMs 32d9951 (PR 52: ESMFold2 noise cap, DPLM2 parity)
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26 days ago
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Sync current FastPLMs source, model cards and dependencies
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Update FastPLMs files
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27 days ago
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Apply coding standards from 1cb5747 (files only)
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Update FastPLMs runtime and cards from 328deef (files only)
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Update FastPLMs runtime and model cards
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Update FastPLMs files
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Update FastPLMs files
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Update FastPLMs files
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Update FastPLMs runtime and model cards
Verified signatureAdd-only FastPLMs files-only publication. Checkpoint weights and complete-artifact attestations are unchanged.9db4a87
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Update FastPLMs runtime files
Verified signatureAdd-only FastPLMs files-only publication. Checkpoint weights and complete-artifact attestations are unchanged.0c84cef -
Update FastPLMs runtime files
Verified signatureAdd-only FastPLMs files-only publication. Checkpoint weights and complete-artifact attestations are unchanged.edb1ddb -
Update FastPLMs runtime files
Verified signatureAdd-only FastPLMs files-only publication. Checkpoint weights and complete-artifact attestations are unchanged.a5f885e