Instructions to use WaveCut/Anima-Preview-3-SDNQ-uint4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use WaveCut/Anima-Preview-3-SDNQ-uint4 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("WaveCut/Anima-Preview-3-SDNQ-uint4", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Cosmos
How to use WaveCut/Anima-Preview-3-SDNQ-uint4 with Cosmos:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
File size: 553 Bytes
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{
"key": "uint4",
"path": "/root/anima-comfy-work/models/Anima-Preview-3-SDNQ-uint4",
"class": "CosmosTransformer3DModel",
"baseline_vram_mib": 509,
"load_seconds": 2.2016136780002853,
"vram_after_load_mib": 1611,
"vram_load_peak_mib": 1611
},
{
"key": "int8",
"path": "/root/anima-comfy-work/models/Anima-Preview-3-SDNQ-int8",
"class": "CosmosTransformer3DModel",
"baseline_vram_mib": 509,
"load_seconds": 12.180104692990426,
"vram_after_load_mib": 2437,
"vram_load_peak_mib": 2437
}
]
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