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_0.bin from calebboud/vicuna: direct link, hf CLI and curl.
- Browser
- Download file 65.5 MB
-
https://huggingface.co/calebboud/vicuna/resolve/main/params_shard_0.bin
- Command line
-
hf download hf://calebboud/vicuna/params_shard_0.bin
-
curl -L -o params_shard_0.bin https://huggingface.co/calebboud/vicuna/resolve/main/params_shard_0.bin
65.5 MB
- Xet hash:
- 51d2260e3b7d034fc81479d2f90e05687bb99663dd1b45a015a0c2571fef96e7
- Size of remote file:
- 65.5 MB
- SHA256:
- 97901915e1c000dc5df8b1eb754ad4e7ccf4a9be8db71a887ac27d0a32f08004
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