Instructions to use unflowerq/CodeLlama-7b-python_code_train_241119 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use unflowerq/CodeLlama-7b-python_code_train_241119 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("unflowerq/CodeLlama-7b-python_code_train_241119", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.safetensors from unflowerq/CodeLlama-7b-python_code_train_241119: direct link, hf CLI and curl.
- Browser
- Download file 134 MB
-
https://huggingface.co/unflowerq/CodeLlama-7b-python_code_train_241119/resolve/main/adapter_model.safetensors
- Command line
-
hf download hf://unflowerq/CodeLlama-7b-python_code_train_241119/adapter_model.safetensors
-
curl -L -o adapter_model.safetensors https://huggingface.co/unflowerq/CodeLlama-7b-python_code_train_241119/resolve/main/adapter_model.safetensors
134 MB
- Xet hash:
- ea3b6f38a6bd68f961694d86b94f1ba012a2d27edf080b26062acbcbf6b70371
- Size of remote file:
- 134 MB
- SHA256:
- 9c08d5eb966cc852f0414c74e3dc07a5f9e9c89cc946701a614a216cf3c4f10b
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