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/45.0 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/45.0
- Command line
-
hf download hf://nvidia/OpenMath-CodeLlama-34b-Python@f7224bf9b0635992989d0a3d0a36b8d16da46509/nemo_model/model_weights/model.decoder.layers.mlp.linear_fc1.layer_norm_weight/45.0
-
curl -L -o 45.0 https://huggingface.co/nvidia/OpenMath-CodeLlama-34b-Python/resolve/f7224bf9b0635992989d0a3d0a36b8d16da46509/nemo_model/model_weights/model.decoder.layers.mlp.linear_fc1.layer_norm_weight/45.0
16.4 kB
- Xet hash:
- ed5bae15ab75aab81833f2732aedaeb2fda7788fa584eb7fa60790e6a3f1be8c
- Size of remote file:
- 16.4 kB
- SHA256:
- 06e3d60634ce0f84d378a0e8775a8a2fb2c28ee750d2355432d9b927e1d7abf7
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