Instructions to use windgrin/q3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use windgrin/q3 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("/data/LLM/Llama-3.2-11B-Vision-Instruct") model = PeftModel.from_pretrained(base_model, "windgrin/q3") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ba927174003e759c0d902d63721466714d9a08d075eef582d61f2713aaece1f7
- Size of remote file:
- 839 MB
- SHA256:
- 43a8e29b57d76092b84e3e910cacd1befef0e239667a7ea85176cf5cd996162d
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