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replied to their post about 16 hours ago
Extending Wan 2.1 generated video - First 14b 720p text to video, then using last frame automatically to to generate a video with 14b 720p image to video - with RIFE 32 FPS 10 second 1280x720p video Our app has this fully automated : https://www.patreon.com/posts/123105403 Here how it works image : https://ibb.co/b582z3R6 Workflow is easy Use your favorite app to generate initial video. Get last frame Give last frame to image to video model - with matching model and resolution Generate And merge Then use MMAudio to add sound I made it automated in my Wan 2.1 app but can be made with ComfyUI easily as well . I can extend as many as times i want :) Here initial video Prompt: Close-up shot of a Roman gladiator, wearing a leather loincloth and armored gloves, standing confidently with a determined expression, holding a sword and shield. The lighting highlights his muscular build and the textures of his worn armor. Negative Prompt: Overexposure, static, blurred details, subtitles, paintings, pictures, still, overall gray, worst quality, low quality, JPEG compression residue, ugly, mutilated, redundant fingers, poorly painted hands, poorly painted faces, deformed, disfigured, deformed limbs, fused fingers, cluttered background, three legs, a lot of people in the background, upside down Used Model: WAN 2.1 14B Text-to-Video Number of Inference Steps: 20 CFG Scale: 6 Sigma Shift: 10 Seed: 224866642 Number of Frames: 81 Denoising Strength: N/A LoRA Model: None TeaCache Enabled: True TeaCache L1 Threshold: 0.15 TeaCache Model ID: Wan2.1-T2V-14B Precision: BF16 Auto Crop: Enabled Final Resolution: 1280x720 Generation Duration: 770.66 seconds
reacted to their post with 🤯 1 day ago
Extending Wan 2.1 generated video - First 14b 720p text to video, then using last frame automatically to to generate a video with 14b 720p image to video - with RIFE 32 FPS 10 second 1280x720p video Our app has this fully automated : https://www.patreon.com/posts/123105403 Here how it works image : https://ibb.co/b582z3R6 Workflow is easy Use your favorite app to generate initial video. Get last frame Give last frame to image to video model - with matching model and resolution Generate And merge Then use MMAudio to add sound I made it automated in my Wan 2.1 app but can be made with ComfyUI easily as well . I can extend as many as times i want :) Here initial video Prompt: Close-up shot of a Roman gladiator, wearing a leather loincloth and armored gloves, standing confidently with a determined expression, holding a sword and shield. The lighting highlights his muscular build and the textures of his worn armor. Negative Prompt: Overexposure, static, blurred details, subtitles, paintings, pictures, still, overall gray, worst quality, low quality, JPEG compression residue, ugly, mutilated, redundant fingers, poorly painted hands, poorly painted faces, deformed, disfigured, deformed limbs, fused fingers, cluttered background, three legs, a lot of people in the background, upside down Used Model: WAN 2.1 14B Text-to-Video Number of Inference Steps: 20 CFG Scale: 6 Sigma Shift: 10 Seed: 224866642 Number of Frames: 81 Denoising Strength: N/A LoRA Model: None TeaCache Enabled: True TeaCache L1 Threshold: 0.15 TeaCache Model ID: Wan2.1-T2V-14B Precision: BF16 Auto Crop: Enabled Final Resolution: 1280x720 Generation Duration: 770.66 seconds
reacted to their post with 🤝 1 day ago
Extending Wan 2.1 generated video - First 14b 720p text to video, then using last frame automatically to to generate a video with 14b 720p image to video - with RIFE 32 FPS 10 second 1280x720p video Our app has this fully automated : https://www.patreon.com/posts/123105403 Here how it works image : https://ibb.co/b582z3R6 Workflow is easy Use your favorite app to generate initial video. Get last frame Give last frame to image to video model - with matching model and resolution Generate And merge Then use MMAudio to add sound I made it automated in my Wan 2.1 app but can be made with ComfyUI easily as well . I can extend as many as times i want :) Here initial video Prompt: Close-up shot of a Roman gladiator, wearing a leather loincloth and armored gloves, standing confidently with a determined expression, holding a sword and shield. The lighting highlights his muscular build and the textures of his worn armor. Negative Prompt: Overexposure, static, blurred details, subtitles, paintings, pictures, still, overall gray, worst quality, low quality, JPEG compression residue, ugly, mutilated, redundant fingers, poorly painted hands, poorly painted faces, deformed, disfigured, deformed limbs, fused fingers, cluttered background, three legs, a lot of people in the background, upside down Used Model: WAN 2.1 14B Text-to-Video Number of Inference Steps: 20 CFG Scale: 6 Sigma Shift: 10 Seed: 224866642 Number of Frames: 81 Denoising Strength: N/A LoRA Model: None TeaCache Enabled: True TeaCache L1 Threshold: 0.15 TeaCache Model ID: Wan2.1-T2V-14B Precision: BF16 Auto Crop: Enabled Final Resolution: 1280x720 Generation Duration: 770.66 seconds
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Extending Wan 2.1 generated video - First 14b 720p text to video, then using last frame automatically to to generate a video with 14b 720p image to video - with RIFE 32 FPS 10 second 1280x720p video

Our app has this fully automated : https://www.patreon.com/posts/123105403

Here how it works image : https://ibb.co/b582z3R6

Workflow is easy

Use your favorite app to generate initial video.

Get last frame

Give last frame to image to video model - with matching model and resolution

Generate

And merge

Then use MMAudio to add sound

I made it automated in my Wan 2.1 app but can be made with ComfyUI easily as well . I can extend as many as times i want :)

Here initial video

Prompt: Close-up shot of a Roman gladiator, wearing a leather loincloth and armored gloves, standing confidently with a determined expression, holding a sword and shield. The lighting highlights his muscular build and the textures of his worn armor.

Negative Prompt: Overexposure, static, blurred details, subtitles, paintings, pictures, still, overall gray, worst quality, low quality, JPEG compression residue, ugly, mutilated, redundant fingers, poorly painted hands, poorly painted faces, deformed, disfigured, deformed limbs, fused fingers, cluttered background, three legs, a lot of people in the background, upside down

Used Model: WAN 2.1 14B Text-to-Video

Number of Inference Steps: 20

CFG Scale: 6

Sigma Shift: 10

Seed: 224866642

Number of Frames: 81

Denoising Strength: N/A

LoRA Model: None

TeaCache Enabled: True

TeaCache L1 Threshold: 0.15

TeaCache Model ID: Wan2.1-T2V-14B

Precision: BF16

Auto Crop: Enabled

Final Resolution: 1280x720

Generation Duration: 770.66 seconds



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