Instructions to use LocalLite/python-code-refactoring-ministral-8B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LocalLite/python-code-refactoring-ministral-8B with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("LocalLite/python-code-refactoring-ministral-8B", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.safetensors from LocalLite/python-code-refactoring-ministral-8B: direct link, hf CLI and curl.
- Browser
- Download file 698 MB
-
https://huggingface.co/LocalLite/python-code-refactoring-ministral-8B/resolve/main/adapter_model.safetensors
- Command line
-
hf download hf://LocalLite/python-code-refactoring-ministral-8B/adapter_model.safetensors
-
curl -L -o adapter_model.safetensors https://huggingface.co/LocalLite/python-code-refactoring-ministral-8B/resolve/main/adapter_model.safetensors
698 MB
- Xet hash:
- efa082fb3523af8b9249a3984ecddcd915832b041f5ac39847d1e6ff42cf6b1a
- Size of remote file:
- 698 MB
- SHA256:
- 0a92443c7e15ac1613c7560b7ee0be7b5378fc1a39e170e8a10fb41b57dcdb4b
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.