Instructions to use afrias5/meta-codellama-34b-python-Feed-78 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use afrias5/meta-codellama-34b-python-Feed-78 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("meta-llama/CodeLlama-34b-Python-hf") model = PeftModel.from_pretrained(base_model, "afrias5/meta-codellama-34b-python-Feed-78") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d4c1009b0ff06df010d711a93dc97a3f1792cedd3c1a02f5aa50fa2476c00055
- Size of remote file:
- 14.5 kB
- SHA256:
- 425605d535b52bf8cda5f055be0bfca994dfa50c246f2bdad5df8e3e11a5cb40
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.