Instructions to use socialtrait/flux-3-image-klein-infendpoint with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use socialtrait/flux-3-image-klein-infendpoint with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("socialtrait/flux-3-image-klein-infendpoint", 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
File size: 405 Bytes
4b33f36 | 1 2 3 4 5 6 7 8 9 10 11 12 13 | """HF Inference Endpoints entry point, same base64 response as the SDXL repo."""
from flux3_engine import Engine
class EndpointHandler:
def __init__(self, path=''):
self.engine = Engine(model_path=path or None)
self.engine.load()
def __call__(self, data):
# HF and the existing persona caller send the legacy SDXL-shaped payload.
return self.engine.legacy(data)
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