Instructions to use HqH1111/Qwen3-VL-2B-Bench2Drive-FrontView with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use HqH1111/Qwen3-VL-2B-Bench2Drive-FrontView with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("image-text-to-text", model="HqH1111/Qwen3-VL-2B-Bench2Drive-FrontView")
messages = [
    {
        "role": "user",
        "content": [
            {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"},
            {"type": "text", "text": "What animal is on the candy?"}
        ]
    },
]
pipe(text=messages)

# Load model directly
from transformers import AutoProcessor, AutoModelForMultimodalLM

processor = AutoProcessor.from_pretrained("HqH1111/Qwen3-VL-2B-Bench2Drive-FrontView")
model = AutoModelForMultimodalLM.from_pretrained("HqH1111/Qwen3-VL-2B-Bench2Drive-FrontView", device_map="auto")
messages = [
    {
        "role": "user",
        "content": [
            {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"},
            {"type": "text", "text": "What animal is on the candy?"}
        ]
    },
]
inputs = processor.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=40)
print(processor.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use HqH1111/Qwen3-VL-2B-Bench2Drive-FrontView with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "HqH1111/Qwen3-VL-2B-Bench2Drive-FrontView"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "HqH1111/Qwen3-VL-2B-Bench2Drive-FrontView",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

Use Docker

docker model run hf.co/HqH1111/Qwen3-VL-2B-Bench2Drive-FrontView

SGLang

How to use HqH1111/Qwen3-VL-2B-Bench2Drive-FrontView with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "HqH1111/Qwen3-VL-2B-Bench2Drive-FrontView" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "HqH1111/Qwen3-VL-2B-Bench2Drive-FrontView",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "HqH1111/Qwen3-VL-2B-Bench2Drive-FrontView" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "HqH1111/Qwen3-VL-2B-Bench2Drive-FrontView",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

Docker Model Runner
How to use HqH1111/Qwen3-VL-2B-Bench2Drive-FrontView with Docker Model Runner:
```
docker model run hf.co/HqH1111/Qwen3-VL-2B-Bench2Drive-FrontView
```

Qwen3-VL-2B — Bench2Drive Front-View Driving VQA (LoRA, merged)

LoRA adaptation of Qwen3-VL-2B-Instruct for front-view autonomous-driving visual question answering on the Bench2Drive (Chat-B2D) benchmark. The vision encoder is frozen; LoRA is applied to the language model + multimodal aligner, then merged back into a single standalone checkpoint.

Input format: front camera current frame + 3 history frames (oldest→newest), with a driving-agent system prompt. Trained on driving data only (no general-domain replay) — this recipe was found to outperform general-mixed and data-scaled variants on both driving and general benchmarks.

Results (held-out front-view QA, n=2,500, deterministic split, zero clip overlap)

Model	Recipe	BLEU-4	ROUGE-L	CIDEr	MMStar
Qwen3-VL-2B (stock)	—	3.00	14.15	0.47	43.67
This model (v7)	B2D-only, 56k, 2 epochs	45.40	74.30	436.4	52.60

General-ability retention (same scorers): AI2D 71.6 · ChartQA 77.2 · RealWorldQA 62.9 · ScienceQA 79.4 · MMStar 52.6 (stock MMStar 43.7 — general reasoning is preserved and, on several benchmarks, improved).

Usage

from transformers import AutoModelForImageTextToText, AutoProcessor
m = AutoModelForImageTextToText.from_pretrained("HqH1111/Qwen3-VL-2B-Bench2Drive-FrontView", torch_dtype="auto", device_map="auto")
p = AutoProcessor.from_pretrained("HqH1111/Qwen3-VL-2B-Bench2Drive-FrontView")

Training

Base Qwen3-VL-2B-Instruct · ViT frozen · LoRA r64/α128 on LLM + aligner · bf16 · 3×A100 · ms-swift. Driving metrics via pycocoevalcap (BLEU-4/ROUGE-L/CIDEr). Non-commercial research use.

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Safetensors

Model size

2B params

Tensor type

BF16

Model tree for HqH1111/Qwen3-VL-2B-Bench2Drive-FrontView

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Qwen/Qwen3-VL-2B-Instruct

Adapter

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