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 Settings
- Draw Things
- DiffusionBee
Commit History
-
Create README.md
Verified signature5c29c37
-
Upload 3 files
Verified signature92b94ac -
Upload folder using huggingface_hub
Verified signature4eec89e -
Upload folder using huggingface_hub
Verified signaturedc3d9a6 -
Upload model_index.json with huggingface_hub
Verified signatureebe7a6d -
Upload folder using huggingface_hub
Verified signatureb2eb396 -
Upload folder using huggingface_hub
Verified signature09c1910 -
Upload folder using huggingface_hub
Verified signature632ecee -
Upload folder using huggingface_hub
Verified signature6f4175c -
Upload folder using huggingface_hub
Verified signaturee6d9282 -
initial commit
Verified signature6805bd0