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:
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- Notebooks
- Google Colab
- Kaggle
Download nemo_model/model_weights/model.decoder.layers.mlp.linear_fc1.layer_norm_weight/.zarray from nvidia/OpenMath-CodeLlama-7b-Python: direct link, hf CLI and curl.
- Browser
- Download file 230 Bytes
-
https://huggingface.co/nvidia/OpenMath-CodeLlama-7b-Python/resolve/main/nemo_model/model_weights/model.decoder.layers.mlp.linear_fc1.layer_norm_weight/.zarray
- Command line
-
hf download hf://nvidia/OpenMath-CodeLlama-7b-Python/nemo_model/model_weights/model.decoder.layers.mlp.linear_fc1.layer_norm_weight/.zarray
-
curl -L -o .zarray https://huggingface.co/nvidia/OpenMath-CodeLlama-7b-Python/resolve/main/nemo_model/model_weights/model.decoder.layers.mlp.linear_fc1.layer_norm_weight/.zarray
230 Bytes
- Xet hash:
- b182e0eaae82af1b8c74282b5c2c91f0cc630e5f193ef4313becdb586aedc8fe
- Size of remote file:
- 230 Bytes
- SHA256:
- 2b7133d0268f56aeb1759633f4a94b185610be536a144bd4866f566a3b80e6cd
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