Instructions to use dimasik2987/5cfff2c9-8115-4ddd-a9aa-0bbe1db9ca91 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use dimasik2987/5cfff2c9-8115-4ddd-a9aa-0bbe1db9ca91 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/Hermes-3-Llama-3.1-8B") model = PeftModel.from_pretrained(base_model, "dimasik2987/5cfff2c9-8115-4ddd-a9aa-0bbe1db9ca91") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0438680c64d5c16e085c7dc0b314689a205795e01e40124175a8af622b5a52a9
- Size of remote file:
- 6.78 kB
- SHA256:
- 7f486870c2c961506ef0a6811e327b515e74bd546659cd2b72b28d656dafd615
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.