Instructions to use basharatwali/CodeLlama-Instruct-Python-7b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use basharatwali/CodeLlama-Instruct-Python-7b with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("basharatwali/CodeLlama-Instruct-Python-7b", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.safetensors from basharatwali/CodeLlama-Instruct-Python-7b: direct link, hf CLI and curl.
- Browser
- Download file 67.1 MB
-
https://huggingface.co/basharatwali/CodeLlama-Instruct-Python-7b/resolve/main/adapter_model.safetensors
- Command line
-
hf download hf://basharatwali/CodeLlama-Instruct-Python-7b/adapter_model.safetensors
-
curl -L -o adapter_model.safetensors https://huggingface.co/basharatwali/CodeLlama-Instruct-Python-7b/resolve/main/adapter_model.safetensors
67.1 MB
- Xet hash:
- 784e55d4c74975a7f72f42e5eb6f683390b9dada02ef1e69104ff30fbbd10476
- Size of remote file:
- 67.1 MB
- SHA256:
- 2744cccc9ff911989664ef5b6902ee0294700bd71a3d2b6b015b852f3fb1a645
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.