Instructions to use CalamitousFelicitousness/Anima-Preview-3-sdnext-diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use CalamitousFelicitousness/Anima-Preview-3-sdnext-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("CalamitousFelicitousness/Anima-Preview-3-sdnext-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 CalamitousFelicitousness/Anima-Preview-3-sdnext-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: 819 Bytes
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license: other
license_name: circlestone-labs-non-commercial
tags:
- text-to-image
- diffusers
- cosmos
library_name: diffusers
pipeline_tag: text-to-image
---
# Anima Preview 3 (SD.Next Diffusers Conversion)
Diffusers-format conversion of [Anima Preview 3](https://huggingface.co/circlestone-labs/Anima) for use with SD.Next.
**Original model:** [circlestone-labs/Anima](https://huggingface.co/circlestone-labs/Anima)
## Changes from Preview 2
- Extended training at 1024 resolution
- Expanded dataset coverage for less common artists (50-100 post count)
## Architecture
- **Transformer:** CosmosTransformer3DModel (2B params, 28 layers)
- **Text Encoder:** Qwen3-0.6B (replacing Cosmos T5-11B)
- **LLM Adapter:** Custom cross-attention adapter bridging Qwen3 to the transformer
- **VAE:** AutoencoderKLWan
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