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:
- 629bf3f4614ecb59e7cdc7bd79cc208fc546650e8ed523a133b9b3ec78e36bbf
- Size of remote file:
- 1.06 kB
- SHA256:
- 3e6421c47c10677889371aa853e78489336313ec7e5a1db02d6066f689103dd9
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.