Feature Extraction
Transformers
Safetensors
aether_rami_moe
biology
chemistry
drug-discovery
ai-drug-discovery
computational-biology
esm2
diffsbdd
structure-based-drug-design
mixture-of-experts
Mixture of Experts
16b
flow-matching
kras-g12c
kras-g12d
tuberculosis
malaria
sickle-cell
pharmacopeia
posebusters
crossdocked2020
custom_code
Instructions to use Premchan369/aether-rami-esm2-diffsbdd with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Premchan369/aether-rami-esm2-diffsbdd with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Premchan369/aether-rami-esm2-diffsbdd", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Premchan369/aether-rami-esm2-diffsbdd", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download checkpoints/graph_models.pt from Premchan369/aether-rami-esm2-diffsbdd: direct link, hf CLI and curl.
- Browser
- Download file 8.36 MB
-
https://huggingface.co/Premchan369/aether-rami-esm2-diffsbdd/resolve/main/checkpoints/graph_models.pt
- Command line
-
hf download hf://Premchan369/aether-rami-esm2-diffsbdd/checkpoints/graph_models.pt
-
curl -L -o graph_models.pt https://huggingface.co/Premchan369/aether-rami-esm2-diffsbdd/resolve/main/checkpoints/graph_models.pt
8.36 MB
- Xet hash:
- 919f7814dbe00bce8e950b31796181245d06c68a18233a8c44a2be782ebd7fcd
- Size of remote file:
- 8.36 MB
- SHA256:
- fef8276edc4b0b712ca18b7a3c7483bfd2c76f25c0f997077703aef76b74682b
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