Instructions to use perilli/OCS_Models with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use perilli/OCS_Models with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("perilli/OCS_Models", 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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CogVideo: Generation\Video
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cogvideox_loras: Conditioning\Video\LoRAs
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embeddings: Conditioning\Image\Embeddings
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```
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CogVideo: Generation\Video
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cogvideox_loras: Conditioning\Video\LoRAs
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embeddings: Conditioning\Image\Embeddings
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model_patches: Patches
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```
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