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
File size: 652 Bytes
58c522e | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 | {
"_class_name": "AutoencoderKL",
"_diffusers_version": "0.20.0.dev0",
"_name_or_path": "FFusion/FFusionXL-BASE",
"act_fn": "silu",
"block_out_channels": [
128,
256,
512,
512
],
"down_block_types": [
"DownEncoderBlock2D",
"DownEncoderBlock2D",
"DownEncoderBlock2D",
"DownEncoderBlock2D"
],
"force_upcast": true,
"in_channels": 3,
"latent_channels": 4,
"layers_per_block": 2,
"norm_num_groups": 32,
"out_channels": 3,
"sample_size": 1024,
"scaling_factor": 0.13025,
"up_block_types": [
"UpDecoderBlock2D",
"UpDecoderBlock2D",
"UpDecoderBlock2D",
"UpDecoderBlock2D"
]
}
|