Instructions to use Eslavath1/dataset.json with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Eslavath1/dataset.json with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("TheBloke/Mistral-7B-Instruct-v0.1-GPTQ") model = PeftModel.from_pretrained(base_model, "Eslavath1/dataset.json") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9c21d0d6e6bb413ed243d95fb2b13bdbbdcb0cef17126215a22b10e94ace03dc
- Size of remote file:
- 7.34 kB
- SHA256:
- 41acb9bb0126c7da62a33a8d903de2cc2d1568c34f80da3cac418153e262cc03
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.