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qwen3-4b-sft-qa
BodyCam-VQA/qwen3-4b-sft-qa
qwen3-4b-sft-qa is a text generation model from BodyCam-VQA. Use it when you need the model to write or continue text. It is set up for peft.
Pre-trained adapters for question generation on police body-worn camera footage, designed to work with Qwen3-4B-Thinking-2507. Trained using standard fine-tuning (SFT).
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Repo size
200 MB
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0
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Repo makeup
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.safetensors189 MB · 92%
At a glance
- Task
- Text Generation
- Library
- peft
- Access
- Public
- Created
- Mar 1, 2026
- Updated
- Mar 5, 2026
- SHA
- 139aedf5
Try a prompt
Base models
Model card
From the Hugging Face model README
Model Card for Model ID
Pre-trained adapters for question generation on police body-worn camera footage, designed to work with Qwen3-4B-Thinking-2507. Trained using standard fine-tuning (SFT).
Usage
bnb_config = BitsAndBytesConfig(
load_in_4bit=True,
bnb_4bit_compute_dtype=torch.float16,
bnb_4bit_use_double_quant=True,
bnb_4bit_quant_type="nf4",
)
model = AutoModelForCausalLM.from_pretrained(
"Qwen/Qwen3-4B-Thinking-2507",
quantization_config=bnb_config,
device_map="auto",
)
self.model = PeftModel.from_pretrained(model, "ADAPTER/PATH", torch_dtype=torch.float16)
Architecture
- Base Model: Qwen3-4B-Thinking-2507
Training
- Trained on high quality investigative questions and the corresponding chain of thought (CoT) tokens generated by Deepseek V3.2 (Reasoner)
Github Repository
Full Codebase: https://github.com/Karish-Gupta/BodyCam-VQA/tree/main/fine_tuning
Framework versions
- PEFT 0.18.1
- Task
- Text Generation
- Library
- peft
- Created
- Mar 1, 2026
- Updated
- Mar 5, 2026