Text-to-Image
Diffusers
Safetensors
English
FluxPipeline
flux
fluxpipeline
schnell
photography
analog
vintage
photorealism
fine-tune
checkpoint
DiffusersPipeline
Instructions to use AlekseyCalvin/mytHSTic-merge_Soonr-Flux_Diffusers_fp8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use AlekseyCalvin/mytHSTic-merge_Soonr-Flux_Diffusers_fp8 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/mytHSTic-merge_Soonr-Flux_Diffusers_fp8", 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
mytHSTic color SOON®: a Fast (3-8 steps) Flux Model by A.C.T. SOON®
A further development of the historic/vintage/analog photo concept also found in my Historic Color Flux LoRAs and Models. This checkpoint merges in, over Pixelwave Schnell V.1, three different Historic Color LoRAS, trained with distinct datasets over different targeted model Layers. Additionally, it lightly merges in a LoRA distillation of STOIQO New Reality by ALIENHAZE and the anti-blur LoRA.
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Model tree for AlekseyCalvin/mytHSTic-merge_Soonr-Flux_Diffusers_fp8
Base model
black-forest-labs/FLUX.1-schnell