Instructions to use ali-vilab/i2vgen-xl with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ali-vilab/i2vgen-xl with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("ali-vilab/i2vgen-xl", 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
Update config.json of UNet to include `attention_head_dim`
Browse files- unet/config.json +1 -0
unet/config.json
CHANGED
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@@ -2,6 +2,7 @@
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"_class_name": "I2VGenXLUNet",
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"_diffusers_version": "0.26.1",
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"_name_or_path": "i2vgen-xl/unet",
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"block_out_channels": [
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320,
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640,
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"_class_name": "I2VGenXLUNet",
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"_diffusers_version": "0.26.1",
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"_name_or_path": "i2vgen-xl/unet",
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+
"attention_head_dim": 64,
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"block_out_channels": [
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320,
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640,
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