Instructions to use MLbackup/T2V_Video_Loras with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use MLbackup/T2V_Video_Loras with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("MLbackup/T2V_Video_Loras", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
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README.md
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Please note, backups are only provided as DEMO files, and are not viable for other generation services without permission.
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<details>
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<summary>Joining the Community</summary>
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Please note, backups are only provided as DEMO files, and are not viable for other generation services without permission.
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Samples:
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<video controls autoplay src="https://cdn-uploads.huggingface.co/production/uploads/63c09b32dd793d5a62895a95/VPlifNwE3QEEdE07eDl_c.mp4"></video>
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<video controls autoplay src="https://cdn-uploads.huggingface.co/production/uploads/63c09b32dd793d5a62895a95/2JZyEVai7ARHK6kbmjjK6.mp4"></video>
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<video controls autoplay src="https://cdn-uploads.huggingface.co/production/uploads/63c09b32dd793d5a62895a95/T6zhO7D-pfJqF1shL14ob.mp4"></video>
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<video controls autoplay src="https://cdn-uploads.huggingface.co/production/uploads/63c09b32dd793d5a62895a95/MWHURoFXxZZ3Lw67GhlVW.mp4"></video>
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<details>
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<summary>Joining the Community</summary>
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