Text-to-Image
Diffusers
ONNX
Safetensors
OpenVINO
English
StableDiffusionXLPipeline
stable-diffusion-xl
stable-diffusion-xl-diffusers
stable-diffusion
di.FFusion.ai
Eval Results (legacy)
Instructions to use FFusion/FFusionXL-BASE with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use FFusion/FFusionXL-BASE with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("FFusion/FFusionXL-BASE", dtype=torch.bfloat16, device_map="cuda") prompt = "a dog in colorful exploding clouds, dreamlike surrealism colorful smoke and fire coming out of it, explosion of data fragments, exploding background,realistic explosion, 3d digital art" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
| { | |
| "_class_name": "StableDiffusionXLPipeline", | |
| "_diffusers_version": "0.20.0.dev0", | |
| "add_watermarker": null, | |
| "force_zeros_for_empty_prompt": true, | |
| "scheduler": [ | |
| "diffusers", | |
| "EulerDiscreteScheduler" | |
| ], | |
| "text_encoder": [ | |
| "transformers", | |
| "CLIPTextModel" | |
| ], | |
| "text_encoder_2": [ | |
| "transformers", | |
| "CLIPTextModelWithProjection" | |
| ], | |
| "tokenizer": [ | |
| "transformers", | |
| "CLIPTokenizer" | |
| ], | |
| "tokenizer_2": [ | |
| "transformers", | |
| "CLIPTokenizer" | |
| ], | |
| "unet": [ | |
| "diffusers", | |
| "UNet2DConditionModel" | |
| ], | |
| "vae": [ | |
| "diffusers", | |
| "AutoencoderKL" | |
| ] | |
| } | |