Instructions to use ritishshrirao/qwen-vqa-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use ritishshrirao/qwen-vqa-lora with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen2.5-VL-3B-Instruct") model = PeftModel.from_pretrained(base_model, "ritishshrirao/qwen-vqa-lora") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 13f20df65b9951a7eee875a7efa257389316d9fdc6208508e0cc2db4e34c665f
- Size of remote file:
- 29.7 MB
- SHA256:
- 9ce49af33a4a0f744527fb4cbed71b354003c3b7b9ec9f146d4a8087e9dd5478
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