Instructions to use nvidia/OpenMath-CodeLlama-34b-Python with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- NeMo
How to use nvidia/OpenMath-CodeLlama-34b-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_fc1.layer_norm_weight/.zarray from nvidia/OpenMath-CodeLlama-34b-Python: direct link, hf CLI and curl.
- Browser
- Download file 230 Bytes
-
https://huggingface.co/nvidia/OpenMath-CodeLlama-34b-Python/resolve/f7224bf9b0635992989d0a3d0a36b8d16da46509/nemo_model/model_weights/model.decoder.layers.mlp.linear_fc1.layer_norm_weight/.zarray
- Command line
-
hf download hf://nvidia/OpenMath-CodeLlama-34b-Python@f7224bf9b0635992989d0a3d0a36b8d16da46509/nemo_model/model_weights/model.decoder.layers.mlp.linear_fc1.layer_norm_weight/.zarray
-
curl -L -o .zarray https://huggingface.co/nvidia/OpenMath-CodeLlama-34b-Python/resolve/f7224bf9b0635992989d0a3d0a36b8d16da46509/nemo_model/model_weights/model.decoder.layers.mlp.linear_fc1.layer_norm_weight/.zarray
230 Bytes
- Xet hash:
- 71f898785a969a00a978081e666e352967e7a53a47e0a9f937ab5490f87ef5c6
- Size of remote file:
- 230 Bytes
- SHA256:
- 5953e124292130f5421f9866cc53e104faeb28045071e5861e77fd712ada6659
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