Feature Extraction
Transformers
Safetensors
roberta_zinc_compression_encoder
chemistry
molecule
custom_code
Instructions to use entropy/roberta_zinc_compression_encoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use entropy/roberta_zinc_compression_encoder with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="entropy/roberta_zinc_compression_encoder", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("entropy/roberta_zinc_compression_encoder", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b79a42ece972541c0e5ec08a941f85c49f0689e83f1214492377a1728c155a71
- Size of remote file:
- 244 MB
- SHA256:
- faa111596c4d62aba81b98d0f33579d7a886a2b931a72d943b28331f4c42e886
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.