Instructions to use cimol/9bede915-74fb-4ce3-95b3-541a1285a782 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use cimol/9bede915-74fb-4ce3-95b3-541a1285a782 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, "cimol/9bede915-74fb-4ce3-95b3-541a1285a782") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 170e420e126410dcb5ef1ef7574d9d00cd5ec4c5349925f26023abeaf49a6dc4
- Size of remote file:
- 6.84 kB
- SHA256:
- dc2b6e12eb76672fef3a13d3e0219a5a560a8e3e52a570766d8019b9257c9595
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.