Instructions to use vidfom/lt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use vidfom/lt with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("vidfom/lt", 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
up
Browse files- gradio_app.py +1 -1
gradio_app.py
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@@ -590,4 +590,4 @@ with gr.Blocks(css=css) as demo:
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concurrency_id="generate_video",
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queue=True,
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)
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demo.launch()
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concurrency_id="generate_video",
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queue=True,
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)
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demo.launch(share=True)
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