Instructions to use GhostScientist/semanticwiki-coder-7b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use GhostScientist/semanticwiki-coder-7b with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("GhostScientist/semanticwiki-coder-7b", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from GhostScientist/semanticwiki-coder-7b: direct link, hf CLI and curl.
- Browser
- Download file 5.84 kB
-
https://huggingface.co/GhostScientist/semanticwiki-coder-7b/resolve/main/training_args.bin
- Command line
-
hf download hf://GhostScientist/semanticwiki-coder-7b/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/GhostScientist/semanticwiki-coder-7b/resolve/main/training_args.bin
5.84 kB
- Xet hash:
- 5558d683dd2ee36085a322ef0fa695425197497c1b3f10547c0e9bd985ae4d10
- Size of remote file:
- 5.84 kB
- SHA256:
- 26ececc418e11f3149124e1575b10d13a4bac958bdb2e683f77638ebc9c28cb8
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.