Instructions to use unflowerq/CodeLlama-7b-python_code_train_2nd_241208 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_2nd_241208 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("unflowerq/CodeLlama-7b-python_code_train_2nd_241208", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.safetensors from unflowerq/CodeLlama-7b-python_code_train_2nd_241208: direct link, hf CLI and curl.
- Browser
- Download file 134 MB
-
https://huggingface.co/unflowerq/CodeLlama-7b-python_code_train_2nd_241208/resolve/main/adapter_model.safetensors
- Command line
-
hf download hf://unflowerq/CodeLlama-7b-python_code_train_2nd_241208/adapter_model.safetensors
-
curl -L -o adapter_model.safetensors https://huggingface.co/unflowerq/CodeLlama-7b-python_code_train_2nd_241208/resolve/main/adapter_model.safetensors
134 MB
- Xet hash:
- 7403036475f890d38f638bf760e17a5efa1b902f2dc312db100e04a7abb51072
- Size of remote file:
- 134 MB
- SHA256:
- db977ba9185506dd525e0e4838de6de042e76a1ac7c5a801b3712999d8badcc0
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