Instructions to use calebboud/vicuna with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use calebboud/vicuna with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("calebboud/vicuna", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download params_shard_17.bin from calebboud/vicuna: direct link, hf CLI and curl.
- Browser
- Download file 31 MB
-
https://huggingface.co/calebboud/vicuna/resolve/main/params_shard_17.bin
- Command line
-
hf download hf://calebboud/vicuna/params_shard_17.bin
-
curl -L -o params_shard_17.bin https://huggingface.co/calebboud/vicuna/resolve/main/params_shard_17.bin
31 MB
- Xet hash:
- fd1ccbcdd2a4d84dc3a8cfb4ab5a96fa08dd126af0f0a080e5a25803133fb146
- Size of remote file:
- 31 MB
- SHA256:
- 6a96501f0e54941ceb02cd549043e5ced7ed2da215f3375615c864c7c0363571
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