Text-to-Image
Diffusers
Safetensors
FluxPipeline
FluxPipeline
FLUXv1-schnell
image-generation
flux-diffusers
art
realism
photography
illustration
anime
full finetune
trained
finetune
trainable
full-finetune
checkpoint
text2image
Schnell
Flux
HSToric
Historic
DiT
transformer
Instructions to use AlekseyCalvin/HyperHistoricColor_FluxDev_Diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use AlekseyCalvin/HyperHistoricColor_FluxDev_Diffusers with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("AlekseyCalvin/HyperHistoricColor_FluxDev_Diffusers", 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
- Draw Things
- DiffusionBee
Herein lives a HF/Diffusers port of our Hyper (accelerated) Flux-Dev-based Hyper Historic Color model.
Find a safetensors version at the link above.
- Downloads last month
- -
Model tree for AlekseyCalvin/HyperHistoricColor_FluxDev_Diffusers
Base model
black-forest-labs/FLUX.1-dev