BLIP3o Pretrain Short Caption: 5 Million Images with Generated Captions

5 million images are each paired with a short caption generated by the Qwen/Qwen2.5-VL-7B-Instruct model. The dataset was created by BLIP3o and last updated on Hugging Face in May 2025. It is intended for pretraining vision-language models.

Use Cases

• Pretraining vision-language models based on the large-scale image-caption pairs.
• Benchmarking image caption generation models based on the synthetic captions.
• Studying the properties of machine-generated captions for image understanding.
• Fine-tuning downstream multimodal tasks using the provided image-text data.

Strengths

• Contains 5 million image-caption pairs, providing substantial scale for model training.
• Captions are generated by a specific, named model (Qwen/Qwen2.5-VL-7B-Instruct), offering consistency in style and length.

Limitations

• Description metadata is limited; actual data quality requires manual inspection after download.
• Column-level documentation is absent; field semantics must be inferred after download.

Provenance

Source

BLIP3o via Hugging Face.

Collection Method

Captions were generated by the Qwen/Qwen2.5-VL-7B-Instruct model.

Time Range

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Freshness

Last updated 2025-05-25 18:10:44; freshness should be verified.

Geography

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