Instructions to use v2ray/Anima-2.9B-preview-v1-diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use v2ray/Anima-2.9B-preview-v1-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("v2ray/Anima-2.9B-preview-v1-diffusers", 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
- Local Apps Settings
- Draw Things
- DiffusionBee
File size: 726 Bytes
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license: other
license_name: circlestone-labs-non-commercial-license
license_link: https://huggingface.co/circlestone-labs/Anima/resolve/main/LICENSE.md
language:
- en
base_model:
- Gazingstars123/Anima-2.9B
library_name: diffusers
pipeline_tag: text-to-image
---
# Anima 2.9B Preview V1 Diffusers
This is a [diffusers](https://github.com/huggingface/diffusers)-loadable version of [Gazingstars123/Anima-2.9B (Preview V1)](https://huggingface.co/Gazingstars123/Anima-2.9B/blob/main/Anima-2.9B-preview-v1.safetensors).
Usage:
```py
import torch
import diffusers
pipeline = diffusers.AnimaModularPipeline.from_pretrained("v2ray/Anima-2.9B-preview-v1-diffusers")
pipeline.load_components(torch_dtype=torch.bfloat16)
```
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