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Qwen2-VL-7B-Instruct

Qwen2-VL 7B is Alibaba's second-generation vision-language model, instruction-tuned to follow text+image prompts. It handles variable-resolution inputs natively and scores competitively against GPT-4V on standard multimodal benchmarks at the 7B scale.

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From the model card

Fields below are copied from the tags and counters on the HuggingFace repository Qwen/Qwen2-VL-7B-Instruct at our last fetch. They are set by the uploader, not verified by us; rows with no tag are omitted. How this page is made.

Publisher (HF namespace)
Qwen
Pipeline tag
image-text-to-text
Library
Transformers
Weight formats
safetensors
License tag
apache-2.0 — read the license file in the repo before relying on it
Lineage
Language tags
English (en)
Papers cited
arXiv:2409.12191, arXiv:2308.12966
Downloads (HF counter at last fetch)
1,254,568
Likes (HF counter at last fetch)
1,285
Model card
https://huggingface.co/Qwen/Qwen2-VL-7B-Instruct

Use cases

  • Document understanding and OCR from scanned images
  • Visual question answering over charts and figures
  • Screenshot-to-code or UI description tasks
  • Multi-image reasoning in a single context window

Pros

  • Native variable-resolution input without cropping
  • Strong OCR and document parsing compared to peers
  • Apache-2.0 license permits commercial use
  • Active inference support on vLLM and text-generation-inference

Cons

  • 7B scale still struggles with fine-grained spatial reasoning
  • Hallucination rate higher than GPT-4V on knowledge-grounded tasks
  • Requires ~16GB VRAM for full bfloat16 serving
  • No audio modality despite the VL name

Tags

transformerssafetensorsqwen2_vlimage-text-to-textmultimodalconversationalenarxiv:2409.12191arxiv:2308.12966base_model:Qwen/Qwen2-VL-7Bbase_model:finetune:Qwen/Qwen2-VL-7Blicense:apache-2.0eval-resultstext-generation-inferenceendpoints_compatibleregion:usdeploy:sagemakerdeploy:azure