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---
license: apache-2.0
language:
- en
base_model:
- Wan-AI/Wan2.1-T2V-14B
pipeline_tag: text-to-video
tags:
- text-to-video
- text-to-image
- lora
- diffusers
- template:diffusion-lora
widget:
- text: >-
cat video A short-haired tabby cat sits on a wooden fence, watching a butterfly flutter in front of it. The cat's ears twitch as it slowly lifts a paw, trying to swipe at the insect. The butterfly lands on its nose for a moment before flying away, leaving the cat slightly confused.
output:
url: example_videos/cat1.mp4
- text: >-
cat video A small orange kitten is jumping up at a dangling toy feather. Each time it leaps, it barely misses, but it keeps trying with determination. Its tail wiggles slightly before each jump, preparing for the next attempt.
output:
url: example_videos/cat2.mp4
- text: >-
ca45t cat video The video features a grey Scottish Fold cat lying on a couch and licking its paw. The cat is lying on its side with its head turned towards the camera. It has a collar on. It is using its front paw to clean its ear.
output:
url: example_videos/cat3.mp4
- text: >-
ca45t cat video A small, white, fluffy, kitten with blue eyes, that looks like a British shorthair, is walking on a grey couch with a white wall behind it. It walks a few steps, and stops to look at something off-camera to its right. Then it resumes walking. The kitten's tail is sticking straight up into the air as it walks.
output:
url: example_videos/cat4.mp4
---
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<h1 style="color: #24292e; margin-top: 0;">Cat LoRA for Wan2.1 14B T2V</h1>
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<h2 style="color: #24292e; margin-top: 0;">Overview</h2>
<p>This LoRA is trained on the Wan2.1 14B T2V model and allows you to generate awesome videos of cats!</p>
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<h2 style="color: #24292e; margin-top: 0;">Features</h2>
<ul style="margin-bottom: 0;">
<li>Trained on the Wan2.1 14B T2V base model</li>
<li>Consistent results across different object types</li>
<li>Simple prompt structure that's easy to adapt</li>
</ul>
</div>
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<h2 style="color: #24292e; margin-top: 0;">Community</h2>
<ul style="margin-bottom: 0;">
<li><b>Discord:</b> <a href="https://discord.com/invite/7tsKMCbNFC" style="color: #0366d6; text-decoration: none;">Join our community</a> to generate videos with this LoRA for free</li>
<li><b>Request LoRAs:</b> We're training and open-sourcing Wan2.1 LoRAs for free - join our Discord to make requests!</li>
</ul>
</div>
</div>
<Gallery />
# Model File and Inference Workflow
## 📥 Download Links:
- [cats_10_epochs.safetensors](./cats_10_epochs.safetensors) - LoRA Model File
- [wan_txt2vid_lora_workflow.json](./workflow/wan_txt2vid_lora_workflow.json) - Wan T2V with LoRA Workflow for ComfyUI
---
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<h2 style="color: #24292e; margin-top: 0;">Recommended Settings</h2>
<ul style="margin-bottom: 0;">
<li><b>LoRA Strength:</b> 1.0</li>
<li><b>Embedded Guidance Scale:</b> 6.0</li>
<li><b>Flow Shift:</b> 5.0</li>
</ul>
</div>
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<h2 style="color: #24292e; margin-top: 0;">Trigger Words</h2>
<p>The key trigger phrase is: <code style="background-color: #f0f0f0; padding: 3px 6px; border-radius: 4px;">ca45t cat video</code></p>
</div>
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<h2 style="color: #24292e; margin-top: 0;">Prompt Template</h2>
<p>For prompting, check out the example prompts; this way of prompting seems to work very well.</p>
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<h2 style="color: #24292e; margin-top: 0;">ComfyUI Workflow</h2>
<p>This LoRA works with a modified version of <a href="https://github.com/kijai/ComfyUI-WanVideoWrapper/blob/main/example_workflows/wanvideo_T2V_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>
<img src="./workflow/workflow_screenshot.png" style="width: 100%; border-radius: 8px; margin: 15px 0; box-shadow: 0 4px 8px rgba(0,0,0,0.1);">
<p>See the Downloads section above for the modified workflow.</p>
</div>
</div>
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<h2 style="color: #24292e; margin-top: 0;">Model Information</h2>
<p>The model weights are available in Safetensors format. See the Downloads section above.</p>
</div>
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<h2 style="color: #24292e; margin-top: 0;">Training Details</h2>
<ul style="margin-bottom: 0;">
<li><b>Base Model:</b> Wan2.1 14B T2V</li>
<li><b>Training Data:</b> Trained on 2 minutes of video comprised of 27 short clips (each clip captioned separately) of cats.</li>
<li><b> Epochs:</b> 10</li>
</ul>
</div>
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<h2 style="color: #24292e; margin-top: 0;">Additional Information</h2>
<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>
</div>
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<h2 style="color: #24292e; margin-top: 0;">Acknowledgments</h2>
<p style="margin-bottom: 0;">Special thanks to Kijai for the ComfyUI Wan Video Wrapper and tdrussell for the training scripts!</p>
</div>
</div>