Text-to-Image
Diffusers
Safetensors
English
StableDiffusionPipeline
stable-diffusion
stable-diffusion-diffusers
Instructions to use tomriddle/anim with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use tomriddle/anim with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("tomriddle/anim", dtype=torch.bfloat16, device_map="cuda") prompt = "masterpiece, best quality, 1girl, brown hair, green eyes, colorful, autumn, cumulonimbus clouds, lighting, blue sky, falling leaves, garden" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
metadata
license: creativeml-openrail-m
thumbnail: >-
https://huggingface.co/cag/anything-v3-1/resolve/main/example-images/thumbnail.png
language:
- en
pipeline_tag: text-to-image
tags:
- stable-diffusion
- stable-diffusion-diffusers
inference: true
widget:
- text: >-
masterpiece, best quality, 1girl, brown hair, green eyes, colorful,
autumn, cumulonimbus clouds, lighting, blue sky, falling leaves, garden
example_title: example 1girl
- text: >-
masterpiece, best quality, 1boy, medium hair, blonde hair, blue eyes,
bishounen, colorful, autumn, cumulonimbus clouds, lighting, blue sky,
falling leaves, garden
example_title: example 1boy
datasets:
- cag/anything-v3-1-dataset
library_name: diffusers