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:
- 8762aac25180146874a4b66e6a2f877ba6c1570e464640edf157cd3004fa07ff
- Size of remote file:
- 14.2 kB
- SHA256:
- 9196a1e708bf24d6abba41cce3f8558820acc3e50f9394c5955e29eb41ffea3d
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