Instructions to use bidit/lamma2-fact_check_v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use bidit/lamma2-fact_check_v1 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-2-7b-hf") model = PeftModel.from_pretrained(base_model, "bidit/lamma2-fact_check_v1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f186d5ba196a17c32a2bb953c8d30952032cd9e7719805227ec82149c7e1358d
- Size of remote file:
- 16.8 MB
- SHA256:
- 477e4a697f171581fa215c639092d0a14085ce888eed8998a559994d7f4b87b9
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.