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
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README.md
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# ESM++
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[ESM++](https://github.com/Synthyra/ESMplusplus) is a faithful implementation of [ESMC](https://www.evolutionaryscale.ai/blog/esm-cambrian) ([license](https://www.evolutionaryscale.ai/policies/cambrian-non-commercial-license-agreement)) that allows for batching and standard Huggingface compatibility without requiring the ESM Python package.
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The large version corresponds to the 600 million parameter version of ESMC.
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# NOTE
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There was previously a bug with Huggingface weight tieing that caused the logits of ESM++ to differ from ESMC. That bug is now resolved.
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# ESM++
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[ESM++](https://github.com/Synthyra/ESMplusplus) is a faithful implementation of [ESMC](https://www.evolutionaryscale.ai/blog/esm-cambrian) ([license](https://www.evolutionaryscale.ai/policies/cambrian-non-commercial-license-agreement)) that allows for batching and standard Huggingface compatibility without requiring the ESM Python package.
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The large version corresponds to the 600 million parameter version of ESMC.
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