Text-to-Image
Diffusers
English
StableDiffusionPipeline
stable-diffusion
stable-diffusion-diffusers
image-to-image
aiart
anime
Instructions to use TheRafal/everything-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use TheRafal/everything-v1 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("TheRafal/everything-v1", 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
| license: creativeml-openrail-m | |
| language: | |
| - en | |
| pipeline_tag: text-to-image | |
| tags: | |
| - stable-diffusion | |
| - stable-diffusion-diffusers | |
| - text-to-image | |
| - diffusers | |
| # Everything V1 | |
| Like other anime-style Stable Diffusion models, it also supports danbooru tags to generate images. | |
| e.g. **_1girl, white hair, golden eyes, beautiful eyes, detail, flower meadow, cumulonimbus clouds, lighting, detailed sky, garden_** | |
| ## 🤗 Diffusers | |
| This model can be used just like any other Stable Diffusion model. For more information, | |
| please have a look at the [Stable Diffusion](https://huggingface.co/docs/diffusers/api/pipelines/stable_diffusion). | |
| You can also export the model to [ONNX](https://huggingface.co/docs/diffusers/optimization/onnx), [MPS](https://huggingface.co/docs/diffusers/optimization/mps) and/or [FLAX/JAX](). | |
| ```python | |
| from diffusers import StableDiffusionPipeline | |
| import torch | |
| model_id = "TheRafal/everything-v1" | |
| branch_name= "main" | |
| pipe = StableDiffusionPipeline.from_pretrained(model_id, revision=branch_name, torch_dtype=torch.float16) | |
| pipe = pipe.to("cuda") | |
| prompt = "1girl, monika \(doki doki literature club\)" | |
| image = pipe(prompt).images[0] | |
| image.save("./monika.png") | |
| ``` | |
| (TODO) |