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_14.bin from calebboud/vicuna: direct link, hf CLI and curl.
- Browser
- Download file 28.3 MB
-
https://huggingface.co/calebboud/vicuna/resolve/main/params_shard_14.bin
- Command line
-
hf download hf://calebboud/vicuna/params_shard_14.bin
-
curl -L -o params_shard_14.bin https://huggingface.co/calebboud/vicuna/resolve/main/params_shard_14.bin
28.3 MB
- Xet hash:
- ec50e79bbe032d795be25a7cdf81dec86ff53ac3a84352c459cac7611f369760
- Size of remote file:
- 28.3 MB
- SHA256:
- 5e342405261af6a21a6b071a6a2f0234112f8f399c10538dcab8b3314d66b36d
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