Instructions to use asimali004/CodeLlamaPython_qfinetuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use asimali004/CodeLlamaPython_qfinetuned with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("asimali004/CodeLlamaPython_qfinetuned", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.safetensors from asimali004/CodeLlamaPython_qfinetuned: direct link, hf CLI and curl.
- Browser
- Download file 67.1 MB
-
https://huggingface.co/asimali004/CodeLlamaPython_qfinetuned/resolve/main/adapter_model.safetensors
- Command line
-
hf download hf://asimali004/CodeLlamaPython_qfinetuned/adapter_model.safetensors
-
curl -L -o adapter_model.safetensors https://huggingface.co/asimali004/CodeLlamaPython_qfinetuned/resolve/main/adapter_model.safetensors
67.1 MB
- Xet hash:
- f7dcc06a46064f0b1a412be07e2e8f126fc0ecde3f9951339a3f40b1deb758d0
- Size of remote file:
- 67.1 MB
- SHA256:
- cd38e1d04ac2869c11be49fa8c83d2a0cf34485778ec82e66e07e6e36dc5467f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.