Instructions to use unflowerq/LLaMa3_2_3B_python_code_train_241119 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use unflowerq/LLaMa3_2_3B_python_code_train_241119 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("unflowerq/LLaMa3_2_3B_python_code_train_241119", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e3f352ccd2ec66da07628565fbf7dc330f6ff31d2107c00052786eb991992303
- Size of remote file:
- 73.4 MB
- SHA256:
- 7c95bc961899a2213225ab85f0803100d69d96840335e6df5e2f899b55efaed9
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.