prithivMLmods/Caption3o-XL-v4
Caption3o-XL-v4 Caption3o-XL-v4 is a large-scale, high-quality image-caption dataset designed for training and evaluating image-to-text models. Derived from prithivMLmods/blip3o-caption-mini-arrow and additional curated sources, this optimized version emphasizes long-form captions and covers a wide range of real-world and artistic scenes. Dataset Summary Format: Parquet Image resolution: 512x512 Languages: English Modality: Image-to-Text License: Apache-2.0… See the full description on the dataset page: https://huggingface.co/datasets/prithivMLmods/Caption3o-XL-v4.
| Author / organization | prithivMLmods |
|---|---|
| License (as declared) | apache-2.0 |
| Downloads | 392 (as reported by Hugging Face) |
| Likes | 3 |
| Created | 15 September 2025 |
| Last updated at source | 15 September 2025 |
Popularity, last 3 days
392 now (-64 since 2026-10-16). Counts as reported by the source, snapshotted daily by Silytics.
Connected in the knowledge graph
- mradermacher/CapQwen3.6-27B-BLIP3o-Long-Caption-Distilled-i1-GGUFModel · used to train
- prithivMLmods/Qwen2-VL-2B-Abliterated-Caption-itModel · used to train
- mradermacher/CapQwen3.6-27B-BLIP3o-Long-Caption-Distilled-GGUFModel · used to train
- mradermacher/Caption3o-XL-2B-Qwen2VL-i1-GGUFModel · used to train
- prithivMLmods/CapQwen3.6-27B-BLIP3o-Long-Caption-Distilled-GGUFModel · used to train
- mradermacher/Qwen2-VL-2B-Abliterated-Caption-it-GGUFModel · used to train
- mradermacher/Qwen2-VL-2B-Abliterated-Caption-it-i1-GGUFModel · used to train
Recent changes
- 17 Oct 2026 Description: Caption3o-XL-v4 Caption3o-XL-v4 is a large-scale, high-quality image-caption dataset designed for training and evaluating image-to-text models. Derived from prithivMLmods/blip3o-caption-mini-arrow and additional curated sources, this optimi → Caption3o-XL-v4 Caption3o-XL-v4 is a large-scale, high-quality image-caption dataset designed for training and evaluating image-to-text models. Derived from prithivMLmods/blip3o-caption-mini-arrow and additional curated sources, this optimi
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