Instructions to use jdopensource/JoyAI-Image-Edit-Plus-Diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use jdopensource/JoyAI-Image-Edit-Plus-Diffusers with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import load_image # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("jdopensource/JoyAI-Image-Edit-Plus-Diffusers", dtype=torch.bfloat16, device_map="cuda") prompt = "Turn this cat into a dog" input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png") image = pipe(image=input_image, prompt=prompt).images[0] - Notebooks
- Google Colab
- Kaggle
Add VDEBench evaluation results
Browse filesHi 👋 this PR adds this model's **[VDEBench](https://huggingface.co/datasets/hongzhuyi/VDEBench)** scores to `.eval_results/`, so they show up on the model page and on the VDEBench leaderboard.
VDEBench evaluates instruction-guided editing of dense English/Chinese document pages (3,506 examples). Each score is the equally weighted mean of IoU, CDM, BLEU-4 and TEDS (0–1, higher is better):
| Task | Score |
|---|---:|
| `local` (edited region, headline) | 0.685 |
| `global` (full page) | 0.673 |
Scores come from the VDEBench paper ([arXiv:2602.00122v4](https://arxiv.org/abs/2602.00122v4), Table 2), and the VDEBench authors confirmed both the values and the evaluated checkpoint ([discussion](https://huggingface.co/datasets/hongzhuyi/VDEBench/discussions/2)).
While this PR is open the scores appear as community-provided; merging it makes them official, and closing it removes them. Docs: https://huggingface.co/docs/hub/eval-results · https://huggingface.co/docs/hub/leaderboard-data-guide
Thanks!
- .eval_results/vdebench.yaml +22 -0
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- dataset:
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id: hongzhuyi/VDEBench
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task_id: local
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value: 0.685
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date: '2026-10-15'
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source:
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url: https://arxiv.org/abs/2602.00122v4
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name: VDEBench paper (v4), Table 2
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user: hongzhuyi
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notes: local setting, n=3,506, PaddleOCR-VL; IoU 0.701, CDM 0.794, BLEU-4 0.472,
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TEDS 0.774
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- dataset:
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id: hongzhuyi/VDEBench
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task_id: global
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value: 0.673
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date: '2026-10-15'
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source:
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url: https://arxiv.org/abs/2602.00122v4
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name: VDEBench paper (v4), Table 2
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user: hongzhuyi
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notes: global setting, n=3,506, PaddleOCR-VL; IoU 0.689, CDM 0.803, BLEU-4 0.430,
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TEDS 0.769
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