kaupane/Inko
text-to-image model by kaupane
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Model card & documentation
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Inko A 0.5B text-to-image model for fine art, in English and Chinese. GitHub & technical report · Try the demo Inko is a text-to-image model trained for painting and illustration across Chinese and Western traditions. Its 532M-parameter flow-matching transformer pairs a curated four-domain art corpus with caption and resolution curricula, chunked Muon optimization on Ascend, and DiffusionART post-training against a self-produced prompt and rubric pool. The full engineering record — data, pretraining, post-training and evaluation — is in the GitHub repository. Release model: the EMA of the specialized post-training run (60 DiffusionART rounds on the completed 300-round main run), built on the 600k pretrained EMA. The pretrained base remains available at tag pretrain-base. All images are generated by the release model at 20 Euler steps and CFG 4.5. Prompts, seeds and canvas sizes are in the manifests (hero1, hero2). The chart compares nine models on five public benchmarks (GenEval, DPG,…
Read the full model card ↗ · Preview checked 2026-10-29T03:48:43.990Z
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Model overview
kaupane/Inko is a text-to-image model repository published by kaupane on Hugging Face. A library was not reported.
This page summarizes Hub metadata. For intended use, training data, evaluation results and limitations, consult the original model card.
Model facts
- Task
- text-to-image
- Library
- Not reported
- Recent downloads (30 days)
- 0
- Cumulative likes
- 1
- Hugging Face trending score
- 1
- Reported safetensors parameters
- 537,104,992
- Architecture
- Not reported
- License
- Not reported — check the model card
- Access
- Not gated by Hugging Face
- Created
- 2026-10-16T06:17:14.000Z
- Last modified
- 2026-10-16T06:38:09.000Z
Compatibility and lineage
Reported languages: en, zh
Base-model lineage was not included.
Parameter count is not a RAM/VRAM requirement. Check precision, quantization, context length and runtime compatibility in the model card; no hardware or API-cost claim is inferred here.
Use and evaluate
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Source and freshness
Source: Hugging Face Hub. Metadata observed 2026-10-16T06:42:25.526Z. Daily imports are snapshots, not real-time monitoring.
Popularity and source listings do not establish security, suitability, licensing rights or benchmark performance.
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