Instructions to use Intel/Cosmos3-Super-int4-AutoRound with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Intel/Cosmos3-Super-int4-AutoRound with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Intel/Cosmos3-Super-int4-AutoRound", torch_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
File size: 553 Bytes
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"_class_name": "Cosmos3OmniDiffusersPipeline",
"_diffusers_version": "0.37.1",
"_name_or_path": "/mnt/disk0/lvl/Cosmos3-Super",
"scheduler": [
"diffusers",
"UniPCMultistepScheduler"
],
"sound_tokenizer": [
"diffusers",
"Cosmos3AVAEAudioTokenizer"
],
"text_tokenizer": [
"transformers",
"Qwen2TokenizerFast"
],
"transformer": [
"diffusers",
"Cosmos3OmniTransformer"
],
"vae": [
"diffusers",
"AutoencoderKLWan"
],
"vision_encoder": [
"transformers",
"Qwen3VLVisionModel"
]
}
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