Instructions to use insilicomedicine/nach0_base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use insilicomedicine/nach0_base with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("insilicomedicine/nach0_base") model = AutoModelForSeq2SeqLM.from_pretrained("insilicomedicine/nach0_base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from insilicomedicine/nach0_base: direct link, hf CLI and curl.
- Browser
- Download file 991 MB
-
https://huggingface.co/insilicomedicine/nach0_base/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://insilicomedicine/nach0_base/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/insilicomedicine/nach0_base/resolve/main/pytorch_model.bin
991 MB
- Xet hash:
- 7ad9cef6f7a295f6ad29dfb2902c2633d582d19d25bfba6de7bfed0489204984
- Size of remote file:
- 991 MB
- SHA256:
- c75cfb4b9bab42f27c3c3d7663736fd5e0e0dd61badd0029a34a05749bed92f9
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.