Instructions to use facebook-llama/custom_code with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook-llama/custom_code with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("facebook-llama/custom_code") model = AutoModel.from_pretrained("facebook-llama/custom_code", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from facebook-llama/custom_code: direct link, hf CLI and curl.
- Browser
- Download file 1.42 GB
-
https://huggingface.co/facebook-llama/custom_code/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://facebook-llama/custom_code/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/facebook-llama/custom_code/resolve/main/pytorch_model.bin
1.42 GB
- Xet hash:
- 433e9584056e5d2ef3de3d6357dfd7ca14cbc4d678686f06b6c4812d0922b62c
- Size of remote file:
- 1.42 GB
- SHA256:
- fd413c1d0f38ef80869b4fb2bb09a03e489c8e94636265f3975c032cb0c4913d
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