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unsloth
/
LTX-2.5-FP8

Text-to-Video
Diffusers
Safetensors
English
LTX2Pipeline
fp8
int8
unsloth
quantized
ltx-2.5
image-to-video
video-generation
Model card Files Files and versions
xet
Community

Instructions to use unsloth/LTX-2.5-FP8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Diffusers

    How to use unsloth/LTX-2.5-FP8 with Diffusers:

    pip install -U diffusers transformers accelerate
    import torch
    from diffusers import DiffusionPipeline
    
    # switch to "mps" for apple devices
    pipe = DiffusionPipeline.from_pretrained("unsloth/LTX-2.5-FP8", dtype=torch.bfloat16, device_map="cuda")
    
    prompt = "A blue humanoid robot with a glowing yellow ring for a face stands in a bright warehouse aisle (INT8-ConvRot)"
    image = pipe(prompt).images[0]
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps Settings
  • Unsloth Desktop
LTX-2.5-FP8
140 GB
Ctrl+K
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  • 1 contributor
History: 1 commit
danielhanchen's picture
danielhanchen
Upload LTX-2.5-FP8
7b40724 1 day ago
  • audio_vae
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  • connectors
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  • diffusion_decoder
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  • duration_head
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  • latent_upsampler
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  • samples
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  • scheduler
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  • text_encoder
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  • tokenizer
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  • transformer
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  • vae
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  • vocoder
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  • .gitattributes
    1.94 kB
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  • LICENSE
    30.4 kB
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  • LTX-2.5-FP8.safetensors
    19.1 GB
    xet
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  • LTX-2.5-INT8-ConvRot.safetensors
    25.1 GB
    xet
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  • LTX-2.5-INT8.safetensors
    25.1 GB
    xet
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  • NOTICE
    828 Bytes
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  • README.md
    31 kB
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  • model_index.json
    971 Bytes
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  • modular_model_index.json
    3.91 kB
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