Instructions to use amztheory/code-python with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use amztheory/code-python with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("tiiuae/falcon-7b") model = PeftModel.from_pretrained(base_model, "amztheory/code-python") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 082760ce39c714b2f52847880b1e3e831bd8955f2a734ea967382423cf44e8c0
- Size of remote file:
- 37.8 MB
- SHA256:
- f96c65e70f8dc3f926283d3bae32439866f8b17af51124acaf6484d59f7cc0ff
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.