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/3.0 from nvidia/OpenMath-CodeLlama-34b-Python: direct link, hf CLI and curl.
- Browser
- Download file 16.4 kB
-
https://huggingface.co/nvidia/OpenMath-CodeLlama-34b-Python/resolve/f7224bf9b0635992989d0a3d0a36b8d16da46509/nemo_model/model_weights/model.decoder.layers.mlp.linear_fc1.layer_norm_weight/3.0
- Command line
-
hf download hf://nvidia/OpenMath-CodeLlama-34b-Python@f7224bf9b0635992989d0a3d0a36b8d16da46509/nemo_model/model_weights/model.decoder.layers.mlp.linear_fc1.layer_norm_weight/3.0
-
curl -L -o 3.0 https://huggingface.co/nvidia/OpenMath-CodeLlama-34b-Python/resolve/f7224bf9b0635992989d0a3d0a36b8d16da46509/nemo_model/model_weights/model.decoder.layers.mlp.linear_fc1.layer_norm_weight/3.0
16.4 kB
- Xet hash:
- f9319c8a5f0bbc32c51aa75bcc5ba85c4052195456f9bc9b2d015921f3f2d35d
- Size of remote file:
- 16.4 kB
- SHA256:
- 70b2d4623438952f3c637d2ecb4ede14816f7067b7f04f8dd2beb510ff444c69
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