How to use from the
Use from the
Diffusers library
pip install -U diffusers transformers accelerate
import torch
from diffusers import DiffusionPipeline

# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("John6666/xe-figure-flux-01-fp8-flux", torch_dtype=torch.bfloat16, device_map="cuda")

prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"
image = pipe(prompt).images[0]

Original model is here.

Use prompt words like:
An anime pvc figure of <...>

This model created by XEZ.

Notice

This is an experimental conversion in Spaces using a homebrew script. serverless Inference API does not currently support torch float8_e4m3fn, so it does not work. I have not been able to confirm if the conversion is working properly. Please consider this as a test run only.

Downloads last month
-
Safetensors
Model size
12B params
Tensor type
F8_E4M3
·
Inference Providers NEW
This model isn't deployed by any Inference Provider. 🙋 Ask for provider support