Instructions to use ctemplin/Llama-3.2-1B-PythonProgrammer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use ctemplin/Llama-3.2-1B-PythonProgrammer with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-3.2-1B-Instruct") model = PeftModel.from_pretrained(base_model, "ctemplin/Llama-3.2-1B-PythonProgrammer") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 39a3666d7a4a796b101f7448a4fd855688e6380d204eb0c1ec89feb30bef8bb2
- Size of remote file:
- 45.1 MB
- SHA256:
- c9b421fae81f4408ca6838e0e3dbb38fb65dc76cb2e9abd12af2d75479e4fc23
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.