Instructions to use UmeAiRT/ComfyUI-Auto-Installer-Assets with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use UmeAiRT/ComfyUI-Auto-Installer-Assets with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("UmeAiRT/ComfyUI-Auto-Installer-Assets", 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
Sync upload model_manifest.json
Browse files- model_manifest.json +127 -0
model_manifest.json
CHANGED
|
@@ -31,6 +31,104 @@
|
|
| 31 |
]
|
| 32 |
}
|
| 33 |
},
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 34 |
"FLUX": {
|
| 35 |
"_family_meta": {
|
| 36 |
"display_name": "FLUX",
|
|
@@ -4634,5 +4732,34 @@
|
|
| 4634 |
}
|
| 4635 |
]
|
| 4636 |
}
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 4637 |
}
|
| 4638 |
}
|
|
|
|
| 31 |
]
|
| 32 |
}
|
| 33 |
},
|
| 34 |
+
"PREPROCESSORS": {
|
| 35 |
+
"_family_meta": {
|
| 36 |
+
"display_name": "Preprocessors",
|
| 37 |
+
"description": "System neural network models for ControlNet preprocessing"
|
| 38 |
+
},
|
| 39 |
+
"Depth": {
|
| 40 |
+
"_meta": {
|
| 41 |
+
"bundle_type": "system",
|
| 42 |
+
"loader_type": "preprocessor"
|
| 43 |
+
},
|
| 44 |
+
"Zoe-N": {
|
| 45 |
+
"min_vram": 0,
|
| 46 |
+
"files": [
|
| 47 |
+
{
|
| 48 |
+
"path": "preprocessors/depth/Intel-zoedepth-nyu-kitti/model.safetensors",
|
| 49 |
+
"path_type": "preprocessors/depth/Intel-zoedepth-nyu-kitti",
|
| 50 |
+
"sha256": "c5494fa0938f18d71e215e245472470c3aefebd7b434abd89750e5ae4008e2",
|
| 51 |
+
"size_mb": 1316
|
| 52 |
+
},
|
| 53 |
+
{
|
| 54 |
+
"path": "preprocessors/depth/Intel-zoedepth-nyu-kitti/config.json",
|
| 55 |
+
"path_type": "preprocessors/depth/Intel-zoedepth-nyu-kitti",
|
| 56 |
+
"sha256": "58494c160c520023c4d5bdeebb3b2d035e37e48cc81225580f49fcb06e175913",
|
| 57 |
+
"size_mb": 0
|
| 58 |
+
},
|
| 59 |
+
{
|
| 60 |
+
"path": "preprocessors/depth/Intel-zoedepth-nyu-kitti/preprocessor_config.json",
|
| 61 |
+
"path_type": "preprocessors/depth/Intel-zoedepth-nyu-kitti",
|
| 62 |
+
"sha256": "0b64d8edc980d7b7abb819085650c43da8b8183acbd4336ab5a9e0e9caf4648e",
|
| 63 |
+
"size_mb": 0
|
| 64 |
+
}
|
| 65 |
+
]
|
| 66 |
+
}
|
| 67 |
+
},
|
| 68 |
+
"Lineart": {
|
| 69 |
+
"_meta": {
|
| 70 |
+
"bundle_type": "system",
|
| 71 |
+
"loader_type": "preprocessor"
|
| 72 |
+
},
|
| 73 |
+
"Standard": {
|
| 74 |
+
"min_vram": 0,
|
| 75 |
+
"files": [
|
| 76 |
+
{
|
| 77 |
+
"path": "preprocessors/lineart/sk_model.pth",
|
| 78 |
+
"path_type": "models_base",
|
| 79 |
+
"sha256": "c686ced2a666b4850b4bb6ccf0748031c3eda9f822de73a34b8979970d90f0c6",
|
| 80 |
+
"size_mb": 140
|
| 81 |
+
},
|
| 82 |
+
{
|
| 83 |
+
"path": "preprocessors/lineart/sk_model2.pth",
|
| 84 |
+
"path_type": "models_base",
|
| 85 |
+
"sha256": "30a534781061f34e83bb9406b4335da4ff2616c95d22a585c1245aa8363e74e0",
|
| 86 |
+
"size_mb": 16
|
| 87 |
+
}
|
| 88 |
+
]
|
| 89 |
+
}
|
| 90 |
+
},
|
| 91 |
+
"SoftEdge": {
|
| 92 |
+
"_meta": {
|
| 93 |
+
"bundle_type": "system",
|
| 94 |
+
"loader_type": "preprocessor"
|
| 95 |
+
},
|
| 96 |
+
"HED": {
|
| 97 |
+
"min_vram": 0,
|
| 98 |
+
"files": [
|
| 99 |
+
{
|
| 100 |
+
"path": "preprocessors/hed/ControlNetHED.pth",
|
| 101 |
+
"path_type": "models_base",
|
| 102 |
+
"sha256": "5ca93762ffd68a29fee1af9d495bf6aab80ae86f08905fb35472a083a4c7a8fa",
|
| 103 |
+
"size_mb": 28
|
| 104 |
+
}
|
| 105 |
+
]
|
| 106 |
+
}
|
| 107 |
+
},
|
| 108 |
+
"Pose": {
|
| 109 |
+
"_meta": {
|
| 110 |
+
"bundle_type": "system",
|
| 111 |
+
"loader_type": "preprocessor"
|
| 112 |
+
},
|
| 113 |
+
"DWPose": {
|
| 114 |
+
"min_vram": 0,
|
| 115 |
+
"files": [
|
| 116 |
+
{
|
| 117 |
+
"path": "preprocessors/dwpose/yolox_l.onnx",
|
| 118 |
+
"path_type": "models_base",
|
| 119 |
+
"sha256": "7860ae79de6c89a3c1eb72ae9a2756c0ccfbe04b7791bb5880afabd97855a411",
|
| 120 |
+
"size_mb": 207
|
| 121 |
+
},
|
| 122 |
+
{
|
| 123 |
+
"path": "preprocessors/dwpose/dw-ll_ucoco_384.onnx",
|
| 124 |
+
"path_type": "models_base",
|
| 125 |
+
"sha256": "724f4ff2439ed61afb86fb8a1951ec39c6220682803b4a8bd4f598cd913b1843",
|
| 126 |
+
"size_mb": 128
|
| 127 |
+
}
|
| 128 |
+
]
|
| 129 |
+
}
|
| 130 |
+
}
|
| 131 |
+
},
|
| 132 |
"FLUX": {
|
| 133 |
"_family_meta": {
|
| 134 |
"display_name": "FLUX",
|
|
|
|
| 4732 |
}
|
| 4733 |
]
|
| 4734 |
}
|
| 4735 |
+
},
|
| 4736 |
+
"_CONTROLNET_MODELS": {
|
| 4737 |
+
"flux-canny-controlnet-v3.safetensors": {
|
| 4738 |
+
"min_vram": 8,
|
| 4739 |
+
"files": [
|
| 4740 |
+
{
|
| 4741 |
+
"path": "controlnet/flux-canny-controlnet-v3.safetensors",
|
| 4742 |
+
"sha256": "6546f29049796101a6370db0a43d2671d0294287c36b2b4e8792cf9e68f0eaf0"
|
| 4743 |
+
}
|
| 4744 |
+
]
|
| 4745 |
+
},
|
| 4746 |
+
"flux-depth-controlnet-v3.safetensors": {
|
| 4747 |
+
"min_vram": 8,
|
| 4748 |
+
"files": [
|
| 4749 |
+
{
|
| 4750 |
+
"path": "controlnet/flux-depth-controlnet-v3.safetensors",
|
| 4751 |
+
"sha256": "d52eeaf8072de89d72b1ee79e3bdc79b5d795ed0a6881a029bbe13d833df7e5f"
|
| 4752 |
+
}
|
| 4753 |
+
]
|
| 4754 |
+
},
|
| 4755 |
+
"controlnet-union-sdxl-1.0.safetensors": {
|
| 4756 |
+
"min_vram": 8,
|
| 4757 |
+
"files": [
|
| 4758 |
+
{
|
| 4759 |
+
"path": "controlnet/controlnet-union-sdxl-1.0.safetensors",
|
| 4760 |
+
"sha256": "a9e13fd61f3193887791c8a0dd07a07202174dc47d5ddaea94ea1344f07c7467"
|
| 4761 |
+
}
|
| 4762 |
+
]
|
| 4763 |
+
}
|
| 4764 |
}
|
| 4765 |
}
|