Feature Extraction
Transformers
Safetensors
fast_esmfold
protein-language-model
fastplms
custom_code
Instructions to use Synthyra/FastESMFold with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Synthyra/FastESMFold with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Synthyra/FastESMFold", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Synthyra/FastESMFold", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 382 Bytes
843a654 2ca20a1 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 | # Direct runtime dependencies for Synthyra/FastESMFold. # FastPLMs source is embedded in this model repository. torch>=2.14 transformers>=5.17 huggingface-hub>=1.32 tokenizers>=0.23 safetensors>=0.8 numpy>=2.5 einops>=0.8 tqdm>=4.70 accelerate>=1.15 biopython>=1.88 biotite>=1.7 brotli>=1.2 msgpack>=1.2 msgpack-numpy>=0.4.8 omegaconf>=2.3 rdkit>=2026.3 scipy>=1.18 zstandard>=0.25 |