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--- |
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license: apache-2.0 |
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language: |
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- en |
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base_model: |
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- Wan-AI/Wan2.1-I2V-14B-480P |
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- Wan-AI/Wan2.1-I2V-14B-480P-Diffusers |
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pipeline_tag: image-to-video |
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tags: |
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- text-to-image |
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- lora |
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- diffusers |
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- template:diffusion-lora |
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- image-to-video |
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widget: |
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- text: >- |
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d011Ye33ect dolly effect. The video begins with a close-up of the man’s steely gaze as he stands in a dusty cemetery, a cigar clenched in his mouth. The camera slowly zooms out, keeping his face centered while the background stretches—revealing crosses, gravestones, and the wide open desert behind him. The dolly effect intensifies the tension of the western standoff. |
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output: |
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url: example_videos/1.mp4 |
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- text: >- |
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d011Ye33ect dolly effect. The video begins with a close-up of the woman's face, her expression calm and confident. As the camera zooms out slowly, her poised figure in the iconic seated position is revealed. The background — a sterile, cold interrogation room — subtly distorts with the dolly effect, enhancing the intensity and drawing focus to her unwavering gaze. |
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output: |
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url: example_videos/2.mp4 |
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- text: >- |
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d011Ye33ect dolly effect. The video begins with a close-up of the man’s intense expression, his mouth open mid-shout. As the camera slowly zooms out, his battle stance and outstretched arms are revealed in full. The dolly effect causes the background of the ancient coliseum to shift and distort slightly, emphasizing the tension and power of the moment. |
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output: |
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url: example_videos/3.mp4 |
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- text: >- |
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d011Ye33ect dolly effect. The video starts with a close-up of the dogs’ faces as they share a single strand of spaghetti. The camera slowly zooms out, revealing the candlelit table, checkered tablecloth, and surrounding alleyway. The dolly effect keeps the dogs centered as the background stretches subtly, enhancing the intimacy of the moment. |
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output: |
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url: example_videos/4.mp4 |
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--- |
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<div style="background-color: #f8f9fa; padding: 20px; border-radius: 10px; margin-bottom: 20px;"> |
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<h1 style="color: #24292e; margin-top: 0;">Dolly Effect LoRA for Wan2.1 14B I2V 480p</h1> |
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<div style="background-color: white; padding: 15px; border-radius: 8px; margin: 15px 0; box-shadow: 0 2px 4px rgba(0,0,0,0.1);"> |
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<h2 style="color: #24292e; margin-top: 0;">Overview</h2> |
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<p>This LoRA is trained on the Wan2.1 14B I2V 480p model and allows you to apply a Dolly zoom camera effect on any image subject! This model also works on T2V, with a very similar prompting style, although the I2V application is more robust.</p> |
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</div> |
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<div style="background-color: white; padding: 15px; border-radius: 8px; margin: 15px 0; box-shadow: 0 2px 4px rgba(0,0,0,0.1);"> |
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<h2 style="color: #24292e; margin-top: 0;">Features</h2> |
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<ul style="margin-bottom: 0;"> |
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<li>Trained on the Wan2.1 14B 480p I2V base model</li> |
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<li>Consistent results across different object types</li> |
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<li>Simple prompt structure that's easy to adapt</li> |
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</ul> |
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</div> |
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<div style="background-color: white; padding: 15px; border-radius: 8px; margin: 15px 0; box-shadow: 0 2px 4px rgba(0,0,0,0.1);"> |
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<h2 style="color: #24292e; margin-top: 0;">Community</h2> |
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<ul style="margin-bottom: 0;"> |
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<li><b>Discord:</b> <a href="https://remade.ai/join-discord?utm_source=Huggingface&utm_medium=Social&utm_campaign=model_release&utm_content=dolly" style="color: #0366d6; text-decoration: none;">Join our community</a> to generate videos with this LoRA for free</li> |
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<li><b>Request LoRAs:</b> We're training and open-sourcing Wan2.1 LoRAs for free - join our Discord to make requests!</li> |
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</ul> |
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</div> |
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</div> |
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<Gallery /> |
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# Model File and Inference Workflow |
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## 📥 Download Links: |
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- [dolly_25_epochs.safetensors](./dolly_25_epochs.safetensors) - LoRA Model File |
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- [wan_img2vid_lora_workflow.json](./workflow_I2V/wan_img2vid_lora_workflow.json) - Wan I2V with LoRA Workflow for ComfyUI |
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--- |
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<div style="background-color: #f8f9fa; padding: 20px; border-radius: 10px; margin-bottom: 20px;"> |
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<div style="background-color: white; padding: 15px; border-radius: 8px; margin: 15px 0; box-shadow: 0 2px 4px rgba(0,0,0,0.1);"> |
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<h2 style="color: #24292e; margin-top: 0;">Recommended Settings</h2> |
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<ul style="margin-bottom: 0;"> |
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<li><b>LoRA Strength:</b> 1.0</li> |
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<li><b>Embedded Guidance Scale:</b> 6.0</li> |
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<li><b>Flow Shift:</b> 5.0</li> |
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</ul> |
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</div> |
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<div style="background-color: white; padding: 15px; border-radius: 8px; margin: 15px 0; box-shadow: 0 2px 4px rgba(0,0,0,0.1);"> |
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<h2 style="color: #24292e; margin-top: 0;">Trigger Words</h2> |
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<p>The key trigger phrase is: <code style="background-color: #f0f0f0; padding: 3px 6px; border-radius: 4px;">d011Ye33ect dolly effect</code></p> |
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</div> |
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<div style="background-color: white; padding: 15px; border-radius: 8px; margin: 15px 0; box-shadow: 0 2px 4px rgba(0,0,0,0.1);"> |
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<h2 style="color: #24292e; margin-top: 0;">Prompt Template</h2> |
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<p>For prompting, check out the example prompts; this way of prompting seems to work very well.</p> |
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<div style="background-color: white; padding: 15px; border-radius: 8px; margin: 15px 0; box-shadow: 0 2px 4px rgba(0,0,0,0.1);"> |
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<h2 style="color: #24292e; margin-top: 0;">ComfyUI Workflow</h2> |
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<p>This LoRA works with a modified version of <a href="https://github.com/kijai/ComfyUI-WanVideoWrapper/blob/main/example_workflows/wanvideo_480p_I2V_example_02.json" style="color: #0366d6; text-decoration: none;">Kijai's Wan Video Wrapper workflow</a>. The main modification is adding a Wan LoRA node connected to the base model.</p> |
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<img src="./workflow_I2V/workflow_screenshot.png" style="width: 100%; border-radius: 8px; margin: 15px 0; box-shadow: 0 4px 8px rgba(0,0,0,0.1);"> |
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<p>See the Downloads section above for the modified workflow.</p> |
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</div> |
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</div> |
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<div style="background-color: #f8f9fa; padding: 20px; border-radius: 10px; margin-bottom: 20px;"> |
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<div style="background-color: white; padding: 15px; border-radius: 8px; margin: 15px 0; box-shadow: 0 2px 4px rgba(0,0,0,0.1);"> |
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<h2 style="color: #24292e; margin-top: 0;">Model Information</h2> |
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<p>The model weights are available in Safetensors format. See the Downloads section above.</p> |
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</div> |
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<div style="background-color: white; padding: 15px; border-radius: 8px; margin: 15px 0; box-shadow: 0 2px 4px rgba(0,0,0,0.1);"> |
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<h2 style="color: #24292e; margin-top: 0;">Training Details</h2> |
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<ul style="margin-bottom: 0;"> |
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<li><b>Base Model:</b> Wan2.1 14B I2V 480p</li> |
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<li><b>Training Data:</b> Trained on 2 minutes of video comprised of 40 short clips (each clip captioned separately) of various dolly effect scenes</li> |
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<li><b> Epochs:</b> 25</li> |
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</ul> |
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</div> |
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<div style="background-color: white; padding: 15px; border-radius: 8px; margin: 15px 0; box-shadow: 0 2px 4px rgba(0,0,0,0.1);"> |
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<h2 style="color: #24292e; margin-top: 0;">Additional Information</h2> |
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<p>Training was done using <a href="https://github.com/tdrussell/diffusion-pipe" style="color: #0366d6; text-decoration: none;">Diffusion Pipe for Training</a></p> |
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</div> |
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<div style="background-color: white; padding: 15px; border-radius: 8px; margin: 15px 0; box-shadow: 0 2px 4px rgba(0,0,0,0.1);"> |
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<h2 style="color: #24292e; margin-top: 0;">Acknowledgments</h2> |
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<p style="margin-bottom: 0;">Special thanks to Kijai for the ComfyUI Wan Video Wrapper and tdrussell for the training scripts!</p> |
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</div> |
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</div> |
