From 355de1c775b51a9ecd7b8fb265d8267947740825 Mon Sep 17 00:00:00 2001 From: kijai <40791699+kijai@users.noreply.github.com> Date: Mon, 10 Mar 2025 21:39:50 +0200 Subject: [PATCH] Create wanvideo_1_3B_control_example_01.json --- .../wanvideo_1_3B_control_example_01.json | 1072 +++++++++++++++++ 1 file changed, 1072 insertions(+) create mode 100644 example_workflows/wanvideo_1_3B_control_example_01.json diff --git a/example_workflows/wanvideo_1_3B_control_example_01.json b/example_workflows/wanvideo_1_3B_control_example_01.json new file mode 100644 index 0000000..e393120 --- /dev/null +++ b/example_workflows/wanvideo_1_3B_control_example_01.json @@ -0,0 +1,1072 @@ +{ + "last_node_id": 106, + "last_link_id": 149, + "nodes": [ + { + "id": 36, + "type": "Note", + "pos": [ + 160, + -1010 + ], + "size": [ + 374.3061828613281, + 171.9547576904297 + ], + "flags": {}, + "order": 0, + "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": 11, + "type": "LoadWanVideoT5TextEncoder", + "pos": [ + 161.7229461669922, + -501.2225036621094 + ], + "size": [ + 377.1661376953125, + 130 + ], + "flags": {}, + "order": 1, + "mode": 0, + "inputs": [], + "outputs": [ + { + "name": "wan_t5_model", + "type": "WANTEXTENCODER", + "links": [ + 15 + ], + "slot_index": 0 + } + ], + "properties": { + "Node name for S&R": "LoadWanVideoT5TextEncoder" + }, + "widgets_values": [ + "umt5-xxl-enc-bf16.safetensors", + "bf16", + "offload_device", + "disabled" + ], + "color": "#332922", + "bgcolor": "#593930" + }, + { + "id": 35, + "type": "WanVideoTorchCompileSettings", + "pos": [ + -276.8500671386719, + -1050.6326904296875 + ], + "size": [ + 390.5999755859375, + 178 + ], + "flags": {}, + "order": 2, + "mode": 0, + "inputs": [], + "outputs": [ + { + "name": "torch_compile_args", + "type": "WANCOMPILEARGS", + "links": [], + "slot_index": 0 + } + ], + "properties": { + "Node name for S&R": "WanVideoTorchCompileSettings" + }, + "widgets_values": [ + "inductor", + false, + "default", + false, + 64, + true + ], + "color": "#223", + "bgcolor": "#335" + }, + { + "id": 44, + "type": "Note", + "pos": [ + -620.9041137695312, + -1049.732421875 + ], + "size": [ + 303.0501403808594, + 88 + ], + "flags": {}, + "order": 3, + "mode": 0, + "inputs": [], + "outputs": [], + "properties": {}, + "widgets_values": [ + "If you have Triton installed, connect this for ~30% speed increase" + ], + "color": "#432", + "bgcolor": "#653" + }, + { + "id": 64, + "type": "WanVideoTorchCompileSettings", + "pos": [ + -276.8500671386719, + -1050.6326904296875 + ], + "size": [ + 390.5999755859375, + 178 + ], + "flags": {}, + "order": 4, + "mode": 0, + "inputs": [], + "outputs": [ + { + "name": "torch_compile_args", + "type": "WANCOMPILEARGS", + "links": [], + "slot_index": 0 + } + ], + "properties": { + "Node name for S&R": "WanVideoTorchCompileSettings" + }, + "widgets_values": [ + "inductor", + false, + "default", + false, + 64, + true + ] + }, + { + "id": 52, + "type": "WanVideoTeaCache", + "pos": [ + 1334.42626953125, + -588.2476196289062 + ], + "size": [ + 315, + 154 + ], + "flags": {}, + "order": 5, + "mode": 0, + "inputs": [], + "outputs": [ + { + "name": "teacache_args", + "type": "TEACACHEARGS", + "links": [ + 103 + ] + } + ], + "properties": { + "Node name for S&R": "WanVideoTeaCache" + }, + "widgets_values": [ + 0.2750000000000001, + 1, + -1, + "offload_device", + "true" + ] + }, + { + "id": 53, + "type": "Note", + "pos": [ + 1329.0076904296875, + -810.7708740234375 + ], + "size": [ + 324.64129638671875, + 159.47401428222656 + ], + "flags": {}, + "order": 6, + "mode": 0, + "inputs": [], + "outputs": [], + "properties": {}, + "widgets_values": [ + "TeaCache could be considered to be sort of an automated step skipper \n\nThe relative l1 threshold -value determines how aggressive this is, higher values are faster but quality suffers more. 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