Instructions to use Monketoo/llama_3.1_code_fixed_try2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Monketoo/llama_3.1_code_fixed_try2 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Monketoo/llama_3.1_code_fixed_try2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3baa4aeb990fbb27c17d8cb5bdd7828e38433398669b972c568984c0b024b61d
- Size of remote file:
- 17.2 MB
- SHA256:
- ea445d0da0bf1567f99949dda9b42a32b6f4179c1719516c9d1a413614deb741
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.