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:
- d61eed9bda7b20a583b8718e87a65314ba532ec0663ea3c331b6532d3281da07
- Size of remote file:
- 74.2 MB
- SHA256:
- 35d0ca1f39b2a00962567a98c655a4cc783913074af1590380c42fcd00b3ef96
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