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WaveCut
/
LingBot-Video-MoE-30B-A3B-SDNQ-uint4-static

Text-to-Video
Diffusers
Safetensors
LingBotVideoPipeline
lingbot-video
sdnq
uint4
8-bit precision
Model card Files Files and versions
xet
Community

Instructions to use WaveCut/LingBot-Video-MoE-30B-A3B-SDNQ-uint4-static with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Diffusers

    How to use WaveCut/LingBot-Video-MoE-30B-A3B-SDNQ-uint4-static with Diffusers:

    pip install -U diffusers transformers accelerate
    import torch
    from diffusers import DiffusionPipeline
    
    # switch to "mps" for apple devices
    pipe = DiffusionPipeline.from_pretrained("WaveCut/LingBot-Video-MoE-30B-A3B-SDNQ-uint4-static", 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
LingBot-Video-MoE-30B-A3B-SDNQ-uint4-static
47.2 GB
Ctrl+K
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  • 1 contributor
History: 5 commits
WaveCut's picture
WaveCut
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206e412 verified about 2 months ago
  • lingbot_sdnq_runtime
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  • processor
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  • refiner
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  • scheduler
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  • text_encoder
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  • transformer
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  • vae
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  • .gitattributes
    1.52 kB
    initial commit about 2 months ago
  • README.md
    11.3 kB
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  • RUNTIME_ADAPTER.md
    995 Bytes
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  • model_index.json
    489 Bytes
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  • model_index.json.bak_lingbot_video_diffusers
    508 Bytes
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  • runtime-requirements.txt
    271 Bytes
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  • scheduling_flow_unipc.py
    33.7 kB
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  • source_revisions.json
    495 Bytes
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