Instructions to use Jeckmu/Qwen2-VL-2B-Instruct-GPTQ-Int4-lora-SurveillanceVideo-250210 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Jeckmu/Qwen2-VL-2B-Instruct-GPTQ-Int4-lora-SurveillanceVideo-250210 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen2-VL-2B-Instruct-GPTQ-Int4") model = PeftModel.from_pretrained(base_model, "Jeckmu/Qwen2-VL-2B-Instruct-GPTQ-Int4-lora-SurveillanceVideo-250210") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 47f88c16dc1b279edef7550d17fa1089b88c3bec018ec466aced15a12a98259a
- Size of remote file:
- 11.4 MB
- SHA256:
- 88a3a6fcb80132f76da8aa40cdc3fccd7e5d8468ef15421f5b0c2715e85217d2
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