Instructions to use havinash-ai/c5feaada-eb55-42bc-9402-2d6bf3824df4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use havinash-ai/c5feaada-eb55-42bc-9402-2d6bf3824df4 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("UCLA-AGI/Gemma-2-9B-It-SPPO-Iter2") model = PeftModel.from_pretrained(base_model, "havinash-ai/c5feaada-eb55-42bc-9402-2d6bf3824df4") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b47976fe74d0b7a0ec00cf5f696a2bb214bd9e875059b3af738c0aed82a08e53
- Size of remote file:
- 55.5 MB
- SHA256:
- 7efb673c6f8d53346a37821515c19007ae0b5abef7dbf43209dd11dc949171e6
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.