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.mlp.linear_fc2.weight/.zarray from nvidia/OpenMath-CodeLlama-7b-Python: direct link, hf CLI and curl.
- Browser
- Download file 259 Bytes
-
https://huggingface.co/nvidia/OpenMath-CodeLlama-7b-Python/resolve/f6d2b510fb499bdc5a680adb8b7b86a6f92155ac/nemo_model/model_weights/model.decoder.layers.mlp.linear_fc2.weight/.zarray
- Command line
-
hf download hf://nvidia/OpenMath-CodeLlama-7b-Python@f6d2b510fb499bdc5a680adb8b7b86a6f92155ac/nemo_model/model_weights/model.decoder.layers.mlp.linear_fc2.weight/.zarray
-
curl -L -o .zarray https://huggingface.co/nvidia/OpenMath-CodeLlama-7b-Python/resolve/f6d2b510fb499bdc5a680adb8b7b86a6f92155ac/nemo_model/model_weights/model.decoder.layers.mlp.linear_fc2.weight/.zarray
259 Bytes
- Xet hash:
- a159748496ce8476a8eafa744eea2c018d02359b7d69f5d1fd360e6d1b1798c0
- Size of remote file:
- 259 Bytes
- SHA256:
- 035d9eeacc570d0d399046e9c0a4a6f52bec039cfdf81afc6979793c330b56c0
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