Update workflow examples to match Comfy Core guidelines
@@ -127,44 +127,154 @@ All workflows have been tested on a 2x 3090 + 1060ti linux setup, a 4070 win 11
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### DisTorch2
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- [Default DisTorch2 Workflow](https://github.com/pollockjj/ComfyUI-MultiGPU/blob/main/examples/distorch2/default_DisTorch2.json)
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||||
- [FLUX.1-dev Example](https://github.com/pollockjj/ComfyUI-MultiGPU/blob/main/examples/distorch2/flux_dev_example_DisTorch2.json)
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- [Hunyuan GGUF Example](https://github.com/pollockjj/ComfyUI-MultiGPU/blob/main/examples/distorch2/hunyuan_gguf_DisTorch2.json)
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||||
- [LTX Video Text-to-Video](https://github.com/pollockjj/ComfyUI-MultiGPU/blob/main/examples/distorch2/ltxv_text_to_video_MultiGPU.json)
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- [Qwen Image Basic Example](https://github.com/pollockjj/ComfyUI-MultiGPU/blob/main/examples/distorch2/qwen_image_basic_example_DisTorch2.json)
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- [WanVideo 2.2 Example](https://github.com/pollockjj/ComfyUI-MultiGPU/blob/main/examples/distorch2/wan2_2_DisTorch2.json)
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<table>
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<tr>
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<td align="center">
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<a href="example_workflows/ltxvideo%20checkpointloadersimple%20distorch2.json">
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<img src="example_workflows/ltxvideo%20checkpointloadersimple%20distorch2.jpg" alt="LTX Video + CheckpointLoaderSimple (DisTorch2)" style="max-width:160px; max-height:160px;">
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<div>LTX Video + CheckpointLoaderSimple (DisTorch2)</div>
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</a>
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</td>
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<td align="center">
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<a href="example_workflows/mochi%20checkpointloaderadvanced%20distorch2.json">
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<img src="example_workflows/mochi%20checkpointloaderadvanced%20distorch2.jpg" alt="Mochi + CheckpointLoaderAdvanced (DisTorch2)" style="max-width:160px; max-height:160px;">
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<div>Mochi + CheckpointLoaderAdvanced (DisTorch2)</div>
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</a>
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</td>
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<td align="center">
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<a href="example_workflows/qwen_image%20unet%20clip%20distorch2.json">
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<img src="example_workflows/qwen_image%20unet%20clip%20distorch2.jpg" alt="Qwen Image UNet + CLIP (DisTorch2)" style="max-width:160px; max-height:160px;">
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<div>Qwen Image UNet + CLIP (DisTorch2)</div>
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</a>
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</td>
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</tr>
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<tr>
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<td align="center">
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<a href="example_workflows/qwen_image_edit_2509%20unet%20clip%20distorch2.json">
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<img src="example_workflows/qwen_image_edit_2509%20unet%20clip%20distorch2.jpg" alt="Qwen Image Edit UNet + CLIP (DisTorch2)" style="max-width:160px; max-height:160px;">
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<div>Qwen Image Edit UNet + CLIP (DisTorch2)</div>
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</a>
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</td>
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<td align="center">
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<a href="example_workflows/wan2_2%20distorch2%20double_unet%20no_cpu.json">
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<img src="example_workflows/wan2_2%20distorch2%20double_unet%20no_cpu.jpg" alt="WanVideo 2.2 Double UNet, No CPU (DisTorch2)" style="max-width:160px; max-height:160px;">
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<div>WanVideo 2.2 Double UNet, No CPU (DisTorch2)</div>
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</a>
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</td>
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<td align="center">
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<a href="example_workflows/wan2_2%20t2i%20lightx2v%20lora%20distorch2.json">
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<img src="example_workflows/wan2_2%20t2i%20lightx2v%20lora%20distorch2.jpg" alt="WanVideo 2.2 T2I LightX2V LoRA (DisTorch2)" style="max-width:160px; max-height:160px;">
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<div>WanVideo 2.2 T2I LightX2V LoRA (DisTorch2)</div>
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</a>
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</td>
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</tr>
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<tr>
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<td align="center">
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<a href="example_workflows/wan2_2%20t2v%20lightx2v%20lora%20distorch2.json">
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<img src="example_workflows/wan2_2%20t2v%20lightx2v%20lora%20distorch2.jpg" alt="WanVideo 2.2 T2V LightX2V LoRA (DisTorch2)" style="max-width:160px; max-height:160px;">
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<div>WanVideo 2.2 T2V LightX2V LoRA (DisTorch2)</div>
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</a>
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</td>
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<td></td>
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<td></td>
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</tr>
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</table>
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### WanVideoWrapper
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- [WanVideo T2V Example](https://github.com/pollockjj/ComfyUI-MultiGPU/blob/main/examples/wannvideowrapper/wanvideo_T2V_example_MultiGPU.json)
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- [WanVideo 2.2 I2V Example](https://github.com/pollockjj/ComfyUI-MultiGPU/blob/main/examples/wannvideowrapper/wanvideo2_2_I2V_A14B_example_WIP_Multigpu.json)
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<table>
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<tr>
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<td align="center">
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<a href="example_workflows/ComfyUI-WanVideoWrapper%20wanvideo_T2V.json">
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<img src="example_workflows/ComfyUI-WanVideoWrapper%20wanvideo_T2V.jpg" alt="WanVideoWrapper T2V" style="max-width:160px; max-height:160px;">
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<div>WanVideoWrapper T2V</div>
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</a>
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</td>
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<td align="center">
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<a href="example_workflows/ComfyUI-WanVideoWrapper%20wanvideo_1_3B%20control_lora.json">
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<img src="example_workflows/ComfyUI-WanVideoWrapper%20wanvideo_1_3B%20control_lora.jpg" alt="WanVideoWrapper 1.3B Control LoRA" style="max-width:160px; max-height:160px;">
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<div>WanVideoWrapper 1.3B Control LoRA</div>
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</a>
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</td>
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<td align="center">
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<a href="example_workflows/ComfyUI-WanVideoWrapper%20wanvideo2_2%20I2V%20A14B%20GGUF.json">
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<img src="example_workflows/ComfyUI-WanVideoWrapper%20wanvideo2_2%20I2V%20A14B%20GGUF.jpg" alt="WanVideoWrapper 2.2 I2V A14B GGUF" style="max-width:160px; max-height:160px;">
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<div>WanVideoWrapper 2.2 I2V A14B GGUF</div>
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</a>
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</td>
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</tr>
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</table>
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### MultiGPU
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- [FLUX.1-dev Example](https://github.com/pollockjj/ComfyUI-MultiGPU/blob/main/examples/multiGPU/flux_dev_example_MultiGPU.json)
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- [SDXL 2-GPU](https://github.com/pollockjj/ComfyUI-MultiGPU/blob/main/examples/multiGPU/sdxl_2gpu.json)
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<table>
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<tr>
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<td align="center">
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<a href="example_workflows/flux%20unet%20dual_clip%20vae%20loaders.json">
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<img src="example_workflows/flux%20unet%20dual_clip%20vae%20loaders.jpg" alt="FLUX UNet + Dual CLIP + VAE Loaders (MultiGPU)" style="max-width:160px; max-height:160px;">
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<div>FLUX UNet + Dual CLIP + VAE Loaders (MultiGPU)</div>
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</a>
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</td>
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<td align="center">
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<a href="example_workflows/sd15%20checkpoint%20loader%20simple.json">
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<img src="example_workflows/sd15%20checkpoint%20loader%20simple.jpg" alt="SD15 CheckpointLoaderSimple (MultiGPU)" style="max-width:160px; max-height:160px;">
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<div>SD15 CheckpointLoaderSimple (MultiGPU)</div>
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</a>
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</td>
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<td align="center">
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<a href="example_workflows/sdxl%20checkpoint%20loader%20advanced.json">
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<img src="example_workflows/sdxl%20checkpoint%20loader%20advanced.jpg" alt="SDXL CheckpointLoaderAdvanced (MultiGPU)" style="max-width:160px; max-height:160px;">
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<div>SDXL CheckpointLoaderAdvanced (MultiGPU)</div>
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</a>
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</td>
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</tr>
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</table>
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### Florence2
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- [Florence2, FLUX.1-dev, LTX Video Pipeline](https://github.com/pollockjj/ComfyUI-MultiGPU/blob/main/examples/florence2/florence2_flux1dev_ltxv_cpu_2gpu.json)
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<table>
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<tr>
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<td align="center">
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<a href="example_workflows/ComfyUI-Florence2%20detailed_caption%20to%20flux.json">
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<img src="example_workflows/ComfyUI-Florence2%20detailed_caption%20to%20flux.jpg" alt="Florence2 Detailed Caption to FLUX Pipeline" style="max-width:160px; max-height:160px;">
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<div>Florence2 Detailed Caption to FLUX Pipeline</div>
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</a>
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</td>
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</tr>
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</table>
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### GGUF
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- [FLUX.1-dev 2-GPU GGUF](https://github.com/pollockjj/ComfyUI-MultiGPU/blob/main/examples/gguf/flux1dev_2gpu_gguf.json)
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- [Hunyuan 2-GPU GGUF](https://github.com/pollockjj/ComfyUI-MultiGPU/blob/main/examples/gguf/hunyuan_2gpu_gguf.json)
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- [Hunyuan CPU+GPU GGUF](https://github.com/pollockjj/ComfyUI-MultiGPU/blob/main/examples/gguf/hunyuan_cpu_1gpu_gguf.json)
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- [Hunyuan GGUF DisTorch](https://github.com/pollockjj/ComfyUI-MultiGPU/blob/main/examples/gguf/hunyuan_gguf_distorch.json)
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- [Hunyuan GGUF MultiGPU](https://github.com/pollockjj/ComfyUI-MultiGPU/blob/main/examples/gguf/hunyuan_gguf_MultiGPU.json)
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<table>
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<tr>
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<td align="center">
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<a href="example_workflows/ComfyUI-GGUF%20flux%20unet%20dual_clip%20loaders.json">
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<img src="example_workflows/ComfyUI-GGUF%20flux%20unet%20dual_clip%20loaders.jpg" alt="FLUX UNet + Dual CLIP GGUF" style="max-width:160px; max-height:160px;">
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<div>FLUX UNet + Dual CLIP GGUF</div>
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</a>
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</td>
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<td align="center">
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<a href="example_workflows/ComfyUI-GGUF%20qwen_image%20unet%20distorch2%20cliploader.json">
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<img src="example_workflows/ComfyUI-GGUF%20qwen_image%20unet%20distorch2%20cliploader.jpg" alt="Qwen Image UNet DisTorch2 GGUF" style="max-width:160px; max-height:160px;">
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<div>Qwen Image UNet DisTorch2 GGUF</div>
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</a>
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</td>
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<td></td>
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</tr>
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</table>
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### HunyuanVideoWrapper
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- [HunyuanVideoWrapper Native VAE](https://github.com/pollockjj/ComfyUI-MultiGPU/blob/main/examples/hunyuanvideowrapper/hunyuanvideowrapper_native_vae.json)
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- [HunyuanVideoWrapper Select Device](https://github.com/pollockjj/ComfyUI-MultiGPU/blob/main/examples/hunyuanvideowrapper/hunyuanvideowrapper_select_device.json)
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### DisTorch (Legacy GGUF)
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- [FLUX.1-dev GGUF DisTorch](https://github.com/pollockjj/ComfyUI-MultiGPU/blob/main/examples/distorch/flux1dev_gguf_distorch.json)
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- [Hunyuan IP2V GGUF DisTorch](https://github.com/pollockjj/ComfyUI-MultiGPU/blob/main/examples/distorch/hunyuan_ip2v_distorch_gguf.json)
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<table>
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<tr>
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<td align="center">
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<a href="example_workflows/hunyuanvideo%20distorch%20DEPRECATED.json">
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<img src="example_workflows/hunyuanvideo%20distorch%20DEPRECATED.jpg" alt="HunyuanVideoWrapper DisTorch (Legacy, Deprecated)" style="max-width:160px; max-height:160px;">
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<div>HunyuanVideoWrapper DisTorch (Legacy, Deprecated)</div>
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</a>
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</td>
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</tr>
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</table>
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## Support
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|
After Width: | Height: | Size: 256 KiB |
|
After Width: | Height: | Size: 231 KiB |
@@ -1,22 +1,97 @@
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||||
{
|
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"id": "3c55bda9-d06f-4dc1-a571-cb6ea8f647e8",
|
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"id": "4d231a10-da3b-4b12-8698-449accd4b87a",
|
||||
"revision": 0,
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||||
"last_node_id": 136,
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"last_link_id": 295,
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"last_node_id": 45,
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||||
"last_link_id": 121,
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||||
"nodes": [
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||||
{
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||||
"id": 16,
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||||
"type": "KSamplerSelect",
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"pos": [
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480,
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912
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],
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"size": [
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315,
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58
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],
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||||
"flags": {},
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"order": 0,
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"mode": 0,
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"inputs": [],
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"outputs": [
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{
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"name": "SAMPLER",
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"type": "SAMPLER",
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||||
"links": [
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19
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]
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}
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],
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"properties": {
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||||
"cnr_id": "comfy-core",
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||||
"ver": "0.3.64",
|
||||
"Node name for S&R": "KSamplerSelect"
|
||||
},
|
||||
"widgets_values": [
|
||||
"euler"
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||||
]
|
||||
},
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||||
{
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||||
"id": 26,
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||||
"type": "FluxGuidance",
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"pos": [
|
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480,
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144
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],
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"size": [
|
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317.4000244140625,
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58
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],
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"flags": {},
|
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"order": 12,
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"mode": 0,
|
||||
"inputs": [
|
||||
{
|
||||
"name": "conditioning",
|
||||
"type": "CONDITIONING",
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||||
"link": 41
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}
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],
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"outputs": [
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||||
{
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||||
"name": "CONDITIONING",
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||||
"type": "CONDITIONING",
|
||||
"slot_index": 0,
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||||
"links": [
|
||||
42
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||||
]
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||||
}
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||||
],
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||||
"properties": {
|
||||
"cnr_id": "comfy-core",
|
||||
"ver": "0.3.64",
|
||||
"Node name for S&R": "FluxGuidance"
|
||||
},
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||||
"widgets_values": [
|
||||
3.5
|
||||
],
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||||
"color": "#233",
|
||||
"bgcolor": "#355"
|
||||
},
|
||||
{
|
||||
"id": 22,
|
||||
"type": "BasicGuider",
|
||||
"pos": [
|
||||
852.2776489257812,
|
||||
-113.5096435546875
|
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576,
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48
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],
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"size": [
|
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222.3482666015625,
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46
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],
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"flags": {},
|
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"order": 10,
|
||||
"order": 13,
|
||||
"mode": 0,
|
||||
"inputs": [
|
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{
|
||||
@@ -41,6 +116,8 @@
|
||||
}
|
||||
],
|
||||
"properties": {
|
||||
"cnr_id": "comfy-core",
|
||||
"ver": "0.3.64",
|
||||
"Node name for S&R": "BasicGuider"
|
||||
},
|
||||
"widgets_values": []
|
||||
@@ -49,15 +126,15 @@
|
||||
"id": 13,
|
||||
"type": "SamplerCustomAdvanced",
|
||||
"pos": [
|
||||
1162.46533203125,
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79.54632568359375
|
||||
864,
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||||
192
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],
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"size": [
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566.427001953125,
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688.7268676757812
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272.3617858886719,
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],
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"flags": {},
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"order": 11,
|
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"order": 14,
|
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"mode": 0,
|
||||
"inputs": [
|
||||
{
|
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@@ -83,7 +160,7 @@
|
||||
{
|
||||
"name": "latent_image",
|
||||
"type": "LATENT",
|
||||
"link": 178
|
||||
"link": 116
|
||||
}
|
||||
],
|
||||
"outputs": [
|
||||
@@ -102,6 +179,8 @@
|
||||
}
|
||||
],
|
||||
"properties": {
|
||||
"cnr_id": "comfy-core",
|
||||
"ver": "0.3.64",
|
||||
"Node name for S&R": "SamplerCustomAdvanced"
|
||||
},
|
||||
"widgets_values": []
|
||||
@@ -110,15 +189,15 @@
|
||||
"id": 25,
|
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"type": "RandomNoise",
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"pos": [
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"size": [
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"flags": {},
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"order": 0,
|
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"order": 1,
|
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"mode": 0,
|
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"inputs": [],
|
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"outputs": [
|
||||
@@ -131,55 +210,86 @@
|
||||
}
|
||||
],
|
||||
"properties": {
|
||||
"cnr_id": "comfy-core",
|
||||
"ver": "0.3.64",
|
||||
"Node name for S&R": "RandomNoise"
|
||||
},
|
||||
"widgets_values": [
|
||||
36218255195780,
|
||||
411099137945992,
|
||||
"randomize"
|
||||
],
|
||||
"color": "#2a363b",
|
||||
"bgcolor": "#3f5159"
|
||||
},
|
||||
{
|
||||
"id": 16,
|
||||
"type": "KSamplerSelect",
|
||||
"id": 30,
|
||||
"type": "ModelSamplingFlux",
|
||||
"pos": [
|
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|
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"size": [
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"flags": {},
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"order": 1,
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"order": 9,
|
||||
"mode": 0,
|
||||
"inputs": [],
|
||||
"inputs": [
|
||||
{
|
||||
"name": "model",
|
||||
"type": "MODEL",
|
||||
"link": 120
|
||||
},
|
||||
{
|
||||
"name": "width",
|
||||
"type": "INT",
|
||||
"widget": {
|
||||
"name": "width"
|
||||
},
|
||||
"link": 115
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"Set cfg to 1.0 for a speed boost at the cost of consistency. Samplers like res_multistep work pretty well at cfg 1.0\n\nThe official number of steps is 50 but I think that's too much. Even just 10 steps seems to work."
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||||
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||||
{
|
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|
||||
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||||
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"A standard FLUX.dev .fp8 UNet to test ComfyUI-MultiGPU Comfy Core Loader basic functionality. In this case we are using standard MultiGPU-wrapped nodes to move model components to their own device.\n\n## Model links\n\n**Diffusion model**\n- [flux1-dev-fp8.safetensors](https://huggingface.co/Comfy-Org/flux1-dev/resolve/main/flux1-dev-fp8.safetensors)\n\n**CLIP**\n- [t5xxl_fp8_e4m3fn_scaled.safetensors](https://huggingface.co/comfyanonymous/flux_text_encoders/resolve/main/t5xxl_fp8_e4m3fn_scaled.safetensors)\n- [clip_l.safetensors](https://huggingface.co/comfyanonymous/flux_text_encoders/resolve/main/clip_l.safetensors)\n\n**VAE**\n- [ae.safetensors](https://huggingface.co/black-forest-labs/FLUX.1-dev/resolve/main/ae.safetensors)\n\nModel Storage Location\n\n```\n📂 ComfyUI/\n├── 📂 models/\n│ ├── 📂 diffusion_models/\n│ │ ├── flux1-dev-fp8.safetensors\n│ ├── 📂 clip/\n│ │ └── t5xxl_fp8_e4m3fn_scaled.safetensors\n│ │ └── clip_l.safetensors\n│ ├── 📂 vae/\n│ │ └── ae.safetensors\n```\n## Device Mapping (Example: Two GPUs, 1 CPU)\n```\n🖥️ system \n├── 🟢 cuda:0\n│ └── flux1-dev-fp8.safetensors\n├── 🟣 cuda:1\n│ └── ae.safetensors\n├── ⚙️ cpu\n └── t5xxl_fp8_e4m3fn_scaled.safetensors\n └── clip_l.safetensors\n```"
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"A DisTorch2 Wan 2.2 workflow where we ignore CPU offloading completely and load both UNets placing blocks on the CPU and CLIP DisTorch2. In this case we are using the DisTorch2 node to statically allocate approximately 70% of the UNet model (13.3G) to the cpu. With `eject_models` being `True`, all other models on the `compute` card (`cuda:0`) will be unloaded, regardless of size, ensuring a clean compute card prior to inference.\n\n## Custom Node\n- [ComfyUI-MultiGPU](https://github.com/pollockjj/ComfyUI-MultiGPU)\n```\n📂 ComfyUI/\n├── 📂 custom_nodes/\n│ ├── 📂 ComfyUI-MultiGPU/\n```\n## Model links\n\n**Diffusion model**\n- [wan2.2_t2v_high_noise_14B_fp8_scaled.safetensors](https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/blob/main/split_files/diffusion_models/wan2.2_t2v_high_noise_14B_fp8_scaled.safetensors)\n- [wan2.2_t2v_low_noise_14B_fp8_scaled.safetensors](https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/blob/main/split_files/diffusion_models/wan2.2_t2v_low_noise_14B_fp8_scaled.safetensors)\n\n**CLIP**\n- [umt5_xxl_fp8_e4m3fn_scaled.safetensors](https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/resolve/main/split_files/text_encoders/umt5_xxl_fp8_e4m3fn_scaled.safetensors)\n\n**VAE**\n- [wan_2.1_vae.safetensors](https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/blob/main/split_files/vae/wan_2.1_vae.safetensors)\n\nModel Storage Location\n\n```\n📂 ComfyUI/\n├── 📂 models/\n│ ├── 📂 clip/\n│ │ └── umt5_xxl_fp8_e4m3fn_scaled.safetensors\n│ ├── 📂 unet/\n│ │ ├── wan2.2_t2v_high_noise_14B_fp8_scaled.safetensors [🟩🟩🟩🟪🟪🟪🟪🟪🟪🟪]\n│ │ ├── wan2.2_t2v_low_noise_14B_fp8_scaled.safetensors [🟩🟩🟩🟪🟪🟪🟪🟪🟪🟪]\n│ ├── 📂 vae/\n│ │ └── qwen_image_vae.safetensors \n```\n## Device Mapping (Example: Two GPUs, 1 CPU)\n```\n🖥️ system \n├── 🟢 cuda:0\n│ └── wan2.2_t2v_high_noise_14B_fp8_scaled.safetensors [🟩🟩🟩]\n│ └── wan2.2_t2v_low_noise_14B_fp8_scaled.safetensors [🟩🟩🟩]\n├── 🟣 cuda:1\n│ └── wan2.2_t2v_high_noise_14B_fp8_scaled.safetensors [🟪🟪🟪🟪🟪🟪🟪]\n│ └── wan2.2_t2v_high_noise_14B_fp8_scaled.safetensors [🟪🟪🟪🟪🟪🟪🟪]\n│ └── umt5_xxl_fp8_e4m3fn_scaled.safetensors\n│ └── wan_2.1_vae.safetensors\n├── ⚙️ cpu\n```"
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"A DisTorch2 Wan 2.2 workflow where we eschew our other `gpu`, offloading both UNets by placing blocks on the `cpu`. In this case we are using the DisTorch2 node to statically allocate approximately 70% of the UNet model (13.3G) to the `cpu`, along with a proportional amount of the LoRAs patched to the model. With `eject_models` being `True`, all other models on the `compute` card (`cuda:0`) will be unloaded, regardless of size, ensuring a clean compute card prior to inference.\n\n## Custom Node\n- [ComfyUI-MultiGPU](https://github.com/pollockjj/ComfyUI-MultiGPU)\n```\n📂 ComfyUI/\n├── 📂 custom_nodes/\n│ ├── 📂 ComfyUI-MultiGPU/\n```\n## Model links\n\n**Diffusion model**\n- [wan2.2_t2v_high_noise_14B_fp8_scaled.safetensors](https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/blob/main/split_files/diffusion_models/wan2.2_t2v_high_noise_14B_fp8_scaled.safetensors)\n- [wan2.2_t2v_low_noise_14B_fp8_scaled.safetensors](https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/blob/main/split_files/diffusion_models/wan2.2_t2v_low_noise_14B_fp8_scaled.safetensors)\n\n**CLIP**\n- [umt5_xxl_fp8_e4m3fn_scaled.safetensors](https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/resolve/main/split_files/text_encoders/umt5_xxl_fp8_e4m3fn_scaled.safetensors)\n\n**VAE**\n- [wan_2.1_vae.safetensors](https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/blob/main/split_files/vae/wan_2.1_vae.safetensors)\n\n**LoRA**\n- [high_noise_model.safetensors](https://huggingface.co/lightx2v/Wan2.2-Lightning/resolve/main/Wan2.2-T2V-A14B-4steps-lora-rank64-Seko-V1.1/high_noise_model.safetensors)\n- [low_noise_model.safetensors](https://huggingface.co/lightx2v/Wan2.2-Lightning/resolve/main/Wan2.2-T2V-A14B-4steps-lora-rank64-Seko-V1.1/low_noise_model.safetensors)\n\n## Model Storage Location\n\n```\n📂 ComfyUI/\n├── 📂 models/\n│ ├── 📂 clip/\n│ │ └── umt5_xxl_fp8_e4m3fn_scaled.safetensors\n│ ├── 📂 unet/\n│ │ ├── wan2.2_t2v_high_noise_14B_fp8_scaled.safetensors [🟩🟩🟩🟪🟪🟪🟪🟪🟪🟪]\n│ │ ├── wan2.2_t2v_low_noise_14B_fp8_scaled.safetensors [🟩🟩🟩🟪🟪🟪🟪🟪🟪🟪]\n│ ├───📂 loras/\n│ ├─────📂 Wan2.2-T2V-A14B-4steps-lora-rank64-Seko-V1.1/\n│ │ ├────── high_noise_model.safetensors [🟩🟩🟩🟪🟪🟪🟪🟪🟪🟪]\n│ │ └────── low_noise_model.safetensors [🟩🟩🟩🟪🟪🟪🟪🟪🟪🟪]\n│ ├── 📂 vae/\n│ │ └── qwen_image_vae.safetensors \n```\n## Device Mapping (Example: Two GPUs, 1 CPU)\n```\n🖥️ system \n├── 🟢 cuda:0\n│ └── wan2.2_t2v_high_noise_14B_fp8_scaled.safetensors [🟩🟩🟩]\n│ └── wan2.2_t2v_low_noise_14B_fp8_scaled.safetensors [🟩🟩🟩]\n│ └── high_noise_model.safetensors [🟩🟩🟩]\n│ └── low_noise_model.safetensors [🟩🟩🟩]\n│ └── umt5_xxl_fp8_e4m3fn_scaled.safetensors\n│ └── wan_2.1_vae.safetensors\n├── 🟣 cuda:1\n│ └── EMPTY\n├── ⚙️ cpu\n └── wan2.2_t2v_high_noise_14B_fp8_scaled.safetensors [🟪🟪🟪🟪🟪🟪🟪]\n └── wan2.2_t2v_low_noise_14B_fp8_scaled.safetensors [🟪🟪🟪🟪🟪🟪🟪]\n └── high_noise_model.safetensors [🟪🟪🟪🟪🟪🟪🟪]\n └── low_noise_model.safetensors [🟪🟪🟪🟪🟪🟪🟪]\n```"
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"A DisTorch2 Wan 2.2 workflow where we ignore CPU offloading completely and load both UNets placing blocks on the CPU and CLIP DisTorch2. In this case we are using the DisTorch2 node to statically allocate approximately 70% of the UNet model (13.3G) to the cpu. With `eject_models` being `True`, all other models on the `compute` card (`cuda:0`) will be unloaded, regardless of size, ensuring a clean compute card prior to inference.\n\n## Custom Node\n- [ComfyUI-MultiGPU](https://github.com/pollockjj/ComfyUI-MultiGPU)\n```\n📂 ComfyUI/\n├── 📂 custom_nodes/\n│ ├── 📂 ComfyUI-MultiGPU/\n```\n## Model links\n\n**Diffusion model**\n- [wan2.2_t2v_high_noise_14B_fp8_scaled.safetensors](https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/blob/main/split_files/diffusion_models/wan2.2_t2v_high_noise_14B_fp8_scaled.safetensors)\n- [wan2.2_t2v_low_noise_14B_fp8_scaled.safetensors](https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/blob/main/split_files/diffusion_models/wan2.2_t2v_low_noise_14B_fp8_scaled.safetensors)\n\n**CLIP**\n- [umt5_xxl_fp8_e4m3fn_scaled.safetensors](https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/resolve/main/split_files/text_encoders/umt5_xxl_fp8_e4m3fn_scaled.safetensors)\n\n**VAE**\n- [wan_2.1_vae.safetensors](https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/blob/main/split_files/vae/wan_2.1_vae.safetensors)\n\nModel Storage Location\n\n```\n📂 ComfyUI/\n├── 📂 models/\n│ ├── 📂 clip/\n│ │ └── umt5_xxl_fp8_e4m3fn_scaled.safetensors\n│ ├── 📂 unet/\n│ │ ├── wan2.2_t2v_high_noise_14B_fp8_scaled.safetensors [🟩🟩🟩🟪🟪🟪🟪🟪🟪🟪]\n│ │ ├── wan2.2_t2v_low_noise_14B_fp8_scaled.safetensors [🟩🟩🟩🟪🟪🟪🟪🟪🟪🟪]\n│ ├── 📂 vae/\n│ │ └── qwen_image_vae.safetensors \n```\n## Device Mapping (Example: Two GPUs, 1 CPU)\n```\n🖥️ system \n├── 🟢 cuda:0\n│ └── wan2.2_t2v_high_noise_14B_fp8_scaled.safetensors [🟩🟩🟩]\n│ └── wan2.2_t2v_low_noise_14B_fp8_scaled.safetensors [🟩🟩🟩]\n├── 🟣 cuda:1\n│ └── wan2.2_t2v_high_noise_14B_fp8_scaled.safetensors [🟪🟪🟪🟪🟪🟪🟪]\n│ └── wan2.2_t2v_high_noise_14B_fp8_scaled.safetensors [🟪🟪🟪🟪🟪🟪🟪]\n│ └── umt5_xxl_fp8_e4m3fn_scaled.safetensors\n│ └── wan_2.1_vae.safetensors\n├── ⚙️ cpu\n```"
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||||
88,
|
||||
29,
|
||||
0,
|
||||
35,
|
||||
0,
|
||||
"MODEL"
|
||||
],
|
||||
[
|
||||
89,
|
||||
29,
|
||||
1,
|
||||
4,
|
||||
0,
|
||||
"CLIP"
|
||||
],
|
||||
[
|
||||
90,
|
||||
29,
|
||||
1,
|
||||
3,
|
||||
0,
|
||||
"CLIP"
|
||||
],
|
||||
[
|
||||
91,
|
||||
44,
|
||||
0,
|
||||
36,
|
||||
0,
|
||||
"MODEL"
|
||||
],
|
||||
[
|
||||
99,
|
||||
50,
|
||||
0,
|
||||
29,
|
||||
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|
||||
"MODEL"
|
||||
],
|
||||
[
|
||||
100,
|
||||
51,
|
||||
0,
|
||||
29,
|
||||
1,
|
||||
"CLIP"
|
||||
],
|
||||
[
|
||||
101,
|
||||
52,
|
||||
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|
||||
44,
|
||||
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|
||||
"MODEL"
|
||||
],
|
||||
[
|
||||
102,
|
||||
55,
|
||||
0,
|
||||
9,
|
||||
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|
||||
"VAE"
|
||||
],
|
||||
[
|
||||
103,
|
||||
9,
|
||||
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|
||||
58,
|
||||
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|
||||
"IMAGE"
|
||||
]
|
||||
],
|
||||
"groups": [],
|
||||
"config": {},
|
||||
"extra": {
|
||||
"ds": {
|
||||
"scale": 0.6410618351739488,
|
||||
"offset": [
|
||||
-1966.2624469350503,
|
||||
1246.7903506223172
|
||||
]
|
||||
},
|
||||
"frontendVersion": "1.27.10",
|
||||
"VHS_latentpreview": false,
|
||||
"VHS_latentpreviewrate": 0,
|
||||
"VHS_MetadataImage": true,
|
||||
"VHS_KeepIntermediate": true
|
||||
},
|
||||
"version": 0.4
|
||||
}
|
||||
@@ -176,12 +176,10 @@ class LTXVLoader:
|
||||
return original_loader._load_vae(weights, config=None)
|
||||
|
||||
class Florence2ModelLoader:
|
||||
@classmethod
|
||||
def INPUT_TYPES(s):
|
||||
all_llm_paths = folder_paths.get_folder_paths("LLM")
|
||||
s.model_paths = create_path_dict(all_llm_paths, lambda x: x.is_dir())
|
||||
|
||||
return {"required": {
|
||||
"model": ([*s.model_paths], {"tooltip": "models are expected to be in Comfyui/models/LLM folder"}),
|
||||
"model": ([item.name for item in Path(folder_paths.models_dir, "LLM").iterdir() if item.is_dir()], {"tooltip": "models are expected to be in Comfyui/models/LLM folder"}),
|
||||
"precision": (['fp16','bf16','fp32'],),
|
||||
"attention": (
|
||||
[ 'flash_attention_2', 'sdpa', 'eager'],
|
||||
|
||||