mirror of
https://github.com/hanzoui/workflow-templates-broken-zap-2026-06-08.git
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2535 lines
68 KiB
JSON
2535 lines
68 KiB
JSON
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"Guide: [Subgraph](https://docs.hanzo.ai/interface/features/subgraph)\n\n## Report issue\n\n- Cannot run / runtime errors: https://github.com/hanzoai/studio/issues\n- UI / frontend issues: https://github.com/hanzoui/frontend/issues\n- Workflow mistakes, wrong params, can't download the models: https://github.com/hanzoui/workflow-templates/issues\n\n\n## Model links\n\n**text_encoders**\n\n- [umt5_xxl_fp8_e4m3fn_scaled.safetensors](https://huggingface.co/hanzoui/Wan_2.1_HanzoStudio_repackaged/resolve/main/split_files/text_encoders/umt5_xxl_fp8_e4m3fn_scaled.safetensors)\n\n**clip_vision**\n\n- [clip_vision_h.safetensors](https://huggingface.co/hanzoui/Wan_2.1_HanzoStudio_repackaged/resolve/main/split_files/clip_vision/clip_vision_h.safetensors)\n\n**loras**\n\n- [chronoedit_distill_lora.safetensors](https://huggingface.co/hanzoui/Wan_2.2_HanzoStudio_Repackaged/resolve/main/split_files/loras/chronoedit_distill_lora.safetensors)\n\n**diffusion_models**\n\n- [chrono_edit_14B_fp16.safetensors](https://huggingface.co/hanzoui/Wan_2.2_HanzoStudio_Repackaged/resolve/main/split_files/diffusion_models/chrono_edit_14B_fp16.safetensors)\n\n**vae**\n\n- [wan_2.1_vae.safetensors](https://huggingface.co/hanzoui/Wan_2.2_HanzoStudio_Repackaged/resolve/main/split_files/vae/wan_2.1_vae.safetensors)\n\n\nModel Storage Location\n\n```\n📂 HanzoStudio/\n├── 📂 models/\n│ ├── 📂 text_encoders/\n│ │ └── umt5_xxl_fp8_e4m3fn_scaled.safetensors\n│ ├── 📂 clip_vision/\n│ │ └── clip_vision_h.safetensors\n│ ├── 📂 loras/\n│ │ └── chronoedit_distill_lora.safetensors\n│ ├── 📂 diffusion_models/\n│ │ └── chrono_edit_14B_fp16.safetensors\n│ └── 📂 vae/\n│ └── wan_2.1_vae.safetensors\n```\n## Aoubt ChronoEdit\n\nChronoEdit-14B is finetuned from the pretrain model of Wan2.1-I2V-14B 720P\n\n[ChronoEdit](https://research.nvidia.com/labs/toronto-ai/chronoedit/), a framework developed by teams from NVIDIA and the University of Toronto, reframes image editing as a two-frame video generation task. It leverages the temporal priors of pretrained video generative models and incorporates a temporal reasoning mechanism to achieve editing results with both visual fidelity and physical consistency. Additionally, it comes with the PBench-Edit benchmark for evaluating physical consistency, making it suitable for scenarios like world simulation that require strict adherence to physical laws."
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