Instructions to use nvidia/OpenMath-CodeLlama-7b-Python with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- NeMo
How to use nvidia/OpenMath-CodeLlama-7b-Python with NeMo:
# tag did not correspond to a valid NeMo domain.
- Notebooks
- Google Colab
- Kaggle
Download nemo_model/model_weights/model.decoder.layers.self_attention.linear_qkv.weight/16.1.0 from nvidia/OpenMath-CodeLlama-7b-Python: direct link, hf CLI and curl.
- Browser
- Download file 25.2 MB
-
https://huggingface.co/nvidia/OpenMath-CodeLlama-7b-Python/resolve/main/nemo_model/model_weights/model.decoder.layers.self_attention.linear_qkv.weight/16.1.0
- Command line
-
hf download hf://nvidia/OpenMath-CodeLlama-7b-Python/nemo_model/model_weights/model.decoder.layers.self_attention.linear_qkv.weight/16.1.0
-
curl -L -o 16.1.0 https://huggingface.co/nvidia/OpenMath-CodeLlama-7b-Python/resolve/main/nemo_model/model_weights/model.decoder.layers.self_attention.linear_qkv.weight/16.1.0
25.2 MB
- Xet hash:
- cd9aa4f7f64d170cca86aa0beb5f832dd25d61af5726cb7e0d2e3a3a799c50f2
- Size of remote file:
- 25.2 MB
- SHA256:
- 73a4fc04ed785510de48d625fe604bffc681a190c31b457537aee7064278fb10
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