Instructions to use FINGU-AI/Qwen2.5-32B-Lora-HQ-e-635 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use FINGU-AI/Qwen2.5-32B-Lora-HQ-e-635 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen2.5-32B-Instruct") model = PeftModel.from_pretrained(base_model, "FINGU-AI/Qwen2.5-32B-Lora-HQ-e-635") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4c1b6cb753ad53c04b1f693e59a0dda34059f42df56e2e2b3dc10df44e16ee93
- Size of remote file:
- 5.5 kB
- SHA256:
- 89677001dcae53eb34c62bd4fd359147dc9fa1f8863bb47ac3eec0335fe11602
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.