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/2.0 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/main/nemo_model/model_weights/model.decoder.layers.mlp.linear_fc1.layer_norm_weight/2.0
- Command line
-
hf download hf://nvidia/OpenMath-CodeLlama-34b-Python/nemo_model/model_weights/model.decoder.layers.mlp.linear_fc1.layer_norm_weight/2.0
-
curl -L -o 2.0 https://huggingface.co/nvidia/OpenMath-CodeLlama-34b-Python/resolve/main/nemo_model/model_weights/model.decoder.layers.mlp.linear_fc1.layer_norm_weight/2.0
16.4 kB
- Xet hash:
- a7c4d7bc29b2a83eefe9d650bcf7aa10d94281dc7ff35d496c94634ee028243b
- Size of remote file:
- 16.4 kB
- SHA256:
- dfa17297797a86eb1ae48d998d0a517d782b7bf4eefc1ffebfa277c3046b783e
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