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README.md
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![image/png](https://cdn-uploads.huggingface.co/production/uploads/62f2bd3bdb7cbd214b658c48/TYKzcKxOjxjX5B3rg1sLc.png)
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## Inference speeds
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We look at various ESM models and their throughput on an H100. Adding efficient batching between ESMC and ESM++ significantly improves the throughput. ESM++ small is even faster than ESM2-35M with long sequences!
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The most gains will be seen with PyTorch > 2.5 on linux machines.
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### Citation
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If you use any of this implementation or work please cite it (as well as the ESMC preprint). Bibtex for both coming soon.
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![image/png](https://cdn-uploads.huggingface.co/production/uploads/62f2bd3bdb7cbd214b658c48/TYKzcKxOjxjX5B3rg1sLc.png)
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## Inference speeds
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We look at various ESM models and their throughput on an H100. Adding efficient batching between ESMC and ESM++ significantly improves the throughput, although ESM++ is also faster than ESMC for batch size one. ESM++ small is even faster than ESM2-35M with long sequences!
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The most gains will be seen with PyTorch > 2.5 on linux machines.
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![image/png](https://cdn-uploads.huggingface.co/production/uploads/62f2bd3bdb7cbd214b658c48/RfLRSchFivdsqJrWMh4bo.png)
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### Citation
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If you use any of this implementation or work please cite it (as well as the ESMC preprint). Bibtex for both coming soon.
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