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... | a red car on a beach | Sahilde kırmızı bir araba | 3,000 | 3 |
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YAML Metadata Warning:The task_categories "image-captioning" is not in the official list: text-classification, token-classification, table-question-answering, question-answering, zero-shot-classification, translation, summarization, feature-extraction, text-generation, fill-mask, sentence-similarity, text-to-speech, text-to-audio, automatic-speech-recognition, audio-to-audio, audio-classification, audio-text-to-text, voice-activity-detection, depth-estimation, image-classification, object-detection, image-segmentation, text-to-image, image-to-text, image-to-image, image-to-video, unconditional-image-generation, video-classification, reinforcement-learning, robotics, tabular-classification, tabular-regression, tabular-to-text, table-to-text, multiple-choice, text-ranking, text-retrieval, time-series-forecasting, text-to-video, image-text-to-text, image-text-to-image, image-text-to-video, visual-question-answering, document-question-answering, zero-shot-image-classification, graph-ml, mask-generation, zero-shot-object-detection, text-to-3d, image-to-3d, image-feature-extraction, video-text-to-text, keypoint-detection, visual-document-retrieval, any-to-any, video-to-video, other
Aurora Mini Diffusion - All Generations
All images generated by AuroraIMG-6M from 10,000 diverse prompts x 20 seeds. Carries English and Turkish captions.
Statistics
| Field | Value |
|---|---|
| Images | 80,696 |
| Unique prompts | 4,035 |
| Resolution | 64x64 |
| Format | JPEG (quality 88) |
| Source | AuroraIMG-6M (AuroraAI-Research) |
Schema
| Column | Type | Description |
|---|---|---|
image |
Image (JPEG) | 64x64 generated image |
caption_en |
string | English prompt used for generation |
caption_tr |
string | Turkish translation of the prompt |
seed |
int | RNG seed used for generation |
prompt_idx |
int | index of the prompt in the generation prompt list |
Generation
Images generated with AuroraIMG-6M (6.8M params, flow matching, Euler, 8 steps, CFG 6.0) from 10,000 diverse English prompts x 20 random seeds.
License
MIT
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