Instructions to use HUBioDataLab/lipo_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HUBioDataLab/lipo_model with Transformers:
# Load model directly from transformers import AutoTokenizer, RobertaForSelfiesClassification tokenizer = AutoTokenizer.from_pretrained("HUBioDataLab/lipo_model") model = RobertaForSelfiesClassification.from_pretrained("HUBioDataLab/lipo_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from HUBioDataLab/lipo_model: direct link, hf CLI and curl.
- Browser
- Download file 349 MB
-
https://huggingface.co/HUBioDataLab/lipo_model/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://HUBioDataLab/lipo_model/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/HUBioDataLab/lipo_model/resolve/main/pytorch_model.bin
349 MB
- Xet hash:
- b2ffb2566328b8bc417651765a04fc9f58ab035875344fc88183e36f200d1a6e
- Size of remote file:
- 349 MB
- SHA256:
- 6b3b51560e9cff09ca9b47178b881764ff5e594c97346769443ee5b9568d55d1
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.