Instructions to use ViTeX-Bench/ViTeX-Edit-14B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ViTeX-Bench/ViTeX-Edit-14B with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("ViTeX-Bench/ViTeX-Edit-14B", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
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README.md
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@@ -20,15 +20,6 @@ Open reference model for **video scene text editing**. Augments Wan2.1-VACE-14B
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> Anonymous release under double-blind review at NeurIPS 2026 Datasets and Benchmarks Track. Author list and DOI updated after deanonymization.
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## Specs
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| Trainable parameters | 4.02 B (VACE blocks + new modules) |
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| New modules | 971 M (GlyphEncoder + 8 × ConditionCrossAttention) |
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| Total inference params | ~24 B (DiT 18.3 B + T5-XXL 5.7 B + Wan VAE 0.13 B) |
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| Resolution / frames / fps | 1280 × 720 / 121 / 24 |
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| Hardware | 1 × NVIDIA H100 / A100 80 GB (~70 GB VRAM) |
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## Repository
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> Anonymous release under double-blind review at NeurIPS 2026 Datasets and Benchmarks Track. Author list and DOI updated after deanonymization.
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## Repository
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