Instructions to use Synthyra/DPLM2-3B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Synthyra/DPLM2-3B with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, EsmForDPLM2 tokenizer = AutoTokenizer.from_pretrained("Synthyra/DPLM2-3B", trust_remote_code=True) model = EsmForDPLM2.from_pretrained("Synthyra/DPLM2-3B", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Update FastPLMs files from Synthyra/FastPLMs 32d9951 (PR 52: ESMFold2 noise cap, DPLM2 parity)
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Give this artifact's bridge its own config and model subclasses (FastPLMs#50)
Verified signatureArtifacts share one FastPLMs runtime per process. Re-exported shared classes let one artifact's model class answer for another with the same config class, for example ESMFold2-300 built as ESMFold2Model after ESMFold2-Fast loaded. Only modeling_fastplms.py changes; the runtime bundle and weights are untouched. https://github.com/Synthyra/FastPLMs/issues/506543c5f
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Sync current FastPLMs source, model cards and dependencies
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Update FastPLMs files
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Update FastPLMs runtime and model cards
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Update FastPLMs runtime files
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Update FastPLMs runtime files
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Update FastPLMs runtime files
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