Feature Extraction
Transformers
PyTorch
Safetensors
boltz2_automodel
protein-language-model
fastplms
custom_code
Instructions to use Synthyra/Boltz2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Synthyra/Boltz2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Synthyra/Boltz2", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Synthyra/Boltz2", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
7 days ago
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Update FastPLMs files from Synthyra/FastPLMs 32d9951 (PR 52: ESMFold2 noise cap, DPLM2 parity)
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24 days ago
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Apply coding standards from 1cb5747 (files only)
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Update FastPLMs runtime and model cards
Verified signaturea645a8c
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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.4c8d0e0
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Update FastPLMs runtime files
Verified signatureAdd-only FastPLMs files-only publication. Checkpoint weights and complete-artifact attestations are unchanged.c65e212