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"comfy-core", "ver": "0.3.26", "Node name for S&R": "CLIPTextEncode" }, "widgets_values": [ "high quality nature video featuring a red panda balancing on a bamboo stem while a bird lands on it's head, on the background there is a waterfall" ] }, { "id": 36, "type": "Note", "pos": [ 160, -1010 ], "size": [ 374.3061828613281, 171.9547576904297 ], "flags": {}, "order": 1, "mode": 0, "inputs": [], "outputs": [], "properties": {}, "widgets_values": [ "fp8_fast seems to cause huge quality degradation\n\nfp_16_fast enables \"Full FP16 Accmumulation in FP16 GEMMs\" feature available in the very latest pytorch nightly, this is around 20% speed boost. \n\nSageattn if you have it installed can be used for almost double inference speed" ], "color": "#432", "bgcolor": "#653" }, { "id": 33, "type": "Note", "pos": [ 170, -1150 ], "size": [ 359.0753479003906, 88 ], "flags": {}, "order": 2, "mode": 0, "inputs": [], "outputs": [], "properties": {}, "widgets_values": [ 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Metadata
Metadata
No metadata found
" ] }, { "id": 42, "type": "Note", "pos": [ -580, -760 ], "size": [ 325.1150207519531, 196.76773071289062 ], "flags": {}, "order": 11, "mode": 0, "inputs": [], "outputs": [], "properties": {}, "widgets_values": [ "Adjust the blocks to swap based on your VRAM, this is a tradeoff between speed and memory usage.\n\nAlternatively there's option to use VRAM management introduced in DiffSynt-Studios. This is usually slower, but saves even more VRAM compared to BlockSwap\n\nFurther VRAM savings are from torch.compile or alternatively using the chunked rope option in the WanVideoSampler -node" ], "color": "#432", "bgcolor": "#653" }, { "id": 44, "type": "Note", "pos": [ -620.9041137695312, -1049.732421875 ], "size": [ 303.0501403808594, 88 ], "flags": {}, "order": 12, "mode": 0, "inputs": [], "outputs": [], "properties": {}, "widgets_values": [ "If you have Triton installed, connect this for ~30% speed increase and reduced peak VRAM usage" ], "color": "#432", "bgcolor": "#653" }, { "id": 27, "type": "WanVideoSampler", "pos": [ 1315.2401123046875, -401.48028564453125 ], "size": [ 315, 927 ], "flags": {}, "order": 23, "mode": 0, "inputs": [ { "name": "model", "type": "WANVIDEOMODEL", "link": 91 }, { "name": "image_embeds", "type": "WANVIDIMAGE_EMBEDS", "link": 66 }, { "name": "text_embeds", "shape": 7, "type": "WANVIDEOTEXTEMBEDS", "link": 30 }, { "name": "samples", "shape": 7, "type": 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