✅ this one → Minimalist T2I Workflow for WAN Video 2.2 (Hugging Face)
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✅ this one → Minimalist T2I Workflow for WAN Video 2.2 (Hugging Face)
✅ Minimalist First-Last Frame to Video Workflow for WAN Video 2.2 (Hugging Face)
🔜 Minimalist FMLF (First-Middle-Last Frame) + Multi Frame Ref To Video Workflow for WAN Video 2.2 (Coming Soon)
🔜 Join Videos (Snippets) – Track Operations, Python Scripting: Be a Storyteller - Seamless Narrative Chain (Coming Soon)
Minimalist T2I Workflow for Wan Video 2.2
A streamlined text-to-image workflow utilizing WAN Video 2.2's High and Low Noise models (14B fp8) for static image generation. This setup deliberately omits the Lighting LoRAs to focus on the base models' capabilities...
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Explicación generada por IA basada en los detalles de la fuente y la configuración. Las sugerencias están claramente identificadas.
Minimalist T2I Workflow for WAN Video 2.2 is for generating static images from text prompts with WAN Video 2.2 high- and low-noise 14B FP8 models.
The listed components include PreviewImage and SaveImage for the described static-image output.
Input: a text prompt describing the image to generate.
Output: a static image, with PreviewImage and SaveImage listed among the components.
GegenDenTag publishes it on Civitai at https://civitai.com/models/2163207.
The page classifies it as Workflows and lists Wan Video 2.2 T2V-A14B as the base model.
The listed model files are umt5_xxl_fp8_e4m3fn_scaled.safetensors, wan_2.1_vae.safetensors, wan2.2_t2v_high_noise_14B_fp8_scaled.safetensors, and wan2.2_t2v_low_noise_14B_fp8_scaled.safetensors.
Core component names include CLIPLoader, CLIPTextEncode, EmptySD3LatentImage, GetNode, KSampler, ModelSamplingSD3, SetNode, and UNETLoader.
Additional component names are MarkdownNote, KSamplerAdvanced, PreviewImage, SaveImage, VAEDecode, and VAELoader.
The published setup omits Lighting LoRAs and additional conditioning through LoRAs and CNet.
It is described for evaluating how the base models represent artistic styles, techniques, and compositions.
Before using it, verify that your environment includes the named model files and components, including wan_2.1_vae.safetensors.
Sugerencia · sin verificar
No release version is provided for this workflow.
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Fuentes
1 fuenteExtractos de fuentes
1 extractoSource context: 197 downloads · Type Workflows · Base model Wan Video 2.2 T2V-A14B
Dare to click the image — opens fixed-size copy.
... Optimized for evaluating the ability to represent artistic styles, techniques, and compositions, without the complexity of additional conditioning through LoRAs and CNet.
Prompting, showcase of different art styles tested with this workflow
Dare to click — opens Civitai Collection .
Requisito de VRAM estimado
Estimación no disponible
Los tamaños de los modelos aún no están lo bastante completos para calcular este requisito.
Requisitos
18 requisitosCLIPLoader
PosibleText encoder · Unknown
umt5_xxl_fp8_e4m3fn_scaled.safetensors
Archivo sin verificarText encoder · Hugging Face · Comfy-Org/Wan_2.1_ComfyUI_repackaged · Comfy-Org/Wan_2.1_ComfyUI_repackaged · Hugging Face
VAEDecode
PosibleVAE · Unknown
VAELoader
PosibleVAE · Unknown
VAE · Hugging Face · Comfy-Org/Wan_2.2_ComfyUI_Repackaged
wan2.2_t2v_high_noise_14B_fp8_scaled.safetensors
Archivo sin verificarCheckpoint · Hugging Face · Comfy-Org/Wan_2.2_ComfyUI_Repackaged · Wan Video 2.2
wan2.2_t2v_low_noise_14B_fp8_scaled.safetensors
Archivo sin verificarCheckpoint · Hugging Face · Comfy-Org/Wan_2.2_ComfyUI_Repackaged · Wan Video 2.2
CLIPTextEncode
PosiblePaquete de nodos · Unknown
EmptySD3LatentImage
No resueltoPaquete de nodos · Unknown
GetNode
No resueltoPaquete de nodos · Unknown
Paquete de nodos · Unknown
KSamplerAdvanced
PosiblePaquete de nodos · Unknown
MarkdownNote
No resueltoPaquete de nodos · Unknown
ModelSamplingSD3
No resueltoPaquete de nodos · Unknown
PreviewImage
PosiblePaquete de nodos · Unknown
SaveImage
PosiblePaquete de nodos · Unknown
SetNode
No resueltoPaquete de nodos · Unknown
UNETLoader
PosiblePaquete de nodos · Unknown