Instructions to use aina-tech/Anima-Lightning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use aina-tech/Anima-Lightning with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("aina-tech/Anima-Lightning", 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 aina-tech/Anima-Lightning 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 Settings
- Draw Things
- DiffusionBee
File size: 594 Bytes
71d78b8 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | # Notice
Anima-Lightning is a 4-step distilled derivative model based on
`circlestone-labs/Anima`, which is itself based on
`nvidia/Cosmos-Predict2-2B-Text2Image`.
This repository contains distilled model weights and is not an official
CircleStone Labs, Comfy Org, or NVIDIA release.
The upstream model is licensed by CircleStone Labs LLC under the CircleStone
Labs Non-Commercial License. See `LICENSE.md` for the full license terms.
Runtime note: this model uses the custom 4-step TDM trajectory documented in
`distilled_generation_config.json`, not the original full-step Anima sampler.
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