Instructions to use WaveCut/Anima-Preview-3-SDNQ-int8-diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use WaveCut/Anima-Preview-3-SDNQ-int8-diffusers 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-int8-diffusers", 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-int8-diffusers 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: 628 Bytes
a80509b a6aa53f a80509b | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 | {
"_class_name": "AnimaTextToImagePipeline",
"_diffusers_version": "0.37.0",
"text_encoder": [
"transformers",
"Qwen3Model"
],
"tokenizer": [
"transformers",
"PreTrainedTokenizerFast"
],
"t5_tokenizer": [
"transformers",
"T5TokenizerFast"
],
"llm_adapter": [
"modeling_llm_adapter",
"AnimaLLMAdapter"
],
"transformer": [
"diffusers",
"CosmosTransformer3DModel"
],
"vae": [
"diffusers",
"AutoencoderKLWan"
],
"scheduler": [
"diffusers",
"FlowMatchEulerDiscreteScheduler"
],
"_name_or_path": "WaveCut/Anima-Preview-3-SDNQ-int8-diffusers"
}
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