Instructions to use andrk9/PIRSData with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use andrk9/PIRSData with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-2-70b-hf") model = PeftModel.from_pretrained(base_model, "andrk9/PIRSData") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a4d87d0d70ffa0c886bf89e47284a3aa61fc6a8f8cd753c3ea1abe0d3fc20ed0
- Size of remote file:
- 65.7 MB
- SHA256:
- 120826b59370d1320fc855be8a66bc4ed0018b13167789cf4c4bdc57459bc50d
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.