Instructions to use Synthyra/ESMplusplus_small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Synthyra/ESMplusplus_small with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Synthyra/ESMplusplus_small", trust_remote_code=True)# Load model directly from transformers import AutoModelForMaskedLM model = AutoModelForMaskedLM.from_pretrained("Synthyra/ESMplusplus_small", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
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README.md
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Measured difference between this implementation and version loaded with ESM package (1000 random sequences)
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Average MSE: 7.742734737803403e-10
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Measured difference between this implementation and version loaded with ESM package (1000 random sequences)
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Average MSE: 7.742734737803403e-10
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