Instructions to use Synthyra/ESMFold2-300 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Synthyra/ESMFold2-300 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Synthyra/ESMFold2-300", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Synthyra/ESMFold2-300", trust_remote_code=True) model = AutoModel.from_pretrained("Synthyra/ESMFold2-300", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download requirements.txt from Synthyra/ESMFold2-300: direct link, hf CLI and curl.
- Browser
- Download file 450 Bytes
-
https://huggingface.co/Synthyra/ESMFold2-300/resolve/main/requirements.txt
- Command line
-
hf download hf://Synthyra/ESMFold2-300/requirements.txt
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curl -L -o requirements.txt https://huggingface.co/Synthyra/ESMFold2-300/resolve/main/requirements.txt
450 Bytes
| # Direct runtime dependencies for Synthyra/ESMFold2-300. | |
| # FastPLMs source is embedded in this model repository. | |
| torch>=2.13,<2.14 | |
| transformers>=5.13,<5.14 | |
| huggingface-hub>=0.34,<2 | |
| tokenizers>=0.22,<0.23 | |
| safetensors>=0.5,<1 | |
| numpy>=1.26,<3 | |
| einops>=0.8,<1 | |
| tqdm>=4.67,<5 | |
| accelerate>=1.10,<2 | |
| biopython>=1.85,<2 | |
| biotite>=1.4,<2 | |
| brotli>=1.1,<2 | |
| msgpack>=1.1,<2 | |
| msgpack-numpy>=0.4.8,<1 | |
| omegaconf>=2.3,<3 | |
| rdkit>=2025.9,<2027 | |
| scipy>=1.15,<2 | |
| zstandard>=0.23,<1 | |