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Check out the documentation for more information.

ImageNet Variations Synth Pilot (1K)

Synthetic vision-language instruction pilot from laion/imagenet_variations prompts.

Pipeline

  1. Sample 1000 prompts from imagenet_variations
  2. Add one style framing per prompt (website / textbook / diagram / …)
  3. Generate image with FLUX.1-schnell
  4. Encode with SEED-2 (<seed2_N>, 32 tokens)
  5. Qwen2.5-VL-7B-Instruct looks at the actual image and writes instruction + response
    (modes: describe / QA / howto / reverse)
  6. Format: capitalized USER / ASSISTANT (synth-llava style)

Format

USER: <seed2> <seed2_N> … </seed2> {instruction} ASSISTANT: {response}

Each JSONL row also has image_path (relative under images/) and metadata (style, mode, base prompt, models).

Contents

Rows 1000
Images 1000 × 1024² PNG under images/
Failures 0

Files

  • data/pilot.jsonl — records
  • images/*.png — generated images (inv_XXXXXX.png)

Notes

Pilot for review before scaling. Intended for VLA / multimodal pretraining research.

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