Instructions to use error577/a1e28f1c-80a3-4aaa-a58f-0cd6cba47922 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use error577/a1e28f1c-80a3-4aaa-a58f-0cd6cba47922 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("MNC-Jihun/Mistral-7B-AO-u0.5-b2-ver0.4") model = PeftModel.from_pretrained(base_model, "error577/a1e28f1c-80a3-4aaa-a58f-0cd6cba47922") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 485edd093bb4cdae5898807dbd9a9e86e9f77df8f7ad44c54309c596508f41f4
- Size of remote file:
- 608 MB
- SHA256:
- dbe3e26d4dbb500a2247c238f1e1a6a0a92e6bb0894d0e8799a8ec9565e9ff68
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.