Instructions to use markod0925/yarn_flux with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use markod0925/yarn_flux with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("markod0925/yarn_flux", 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
metadata
library_name: diffusers
datasets:
- Norod78/Yarn-art-style
base_model:
- black-forest-labs/FLUX.1-dev
Model Card for Model ID
Make everything as Yarn Art Syle.
Uses
Make everything as Yarn Art Syle.
How to Get Started with the Model
!pip install -U diffusers bitsandbytes
from diffusers import AutoPipelineForText2Image, BitsAndBytesConfig
import torch
repo_id = "markod0925/yarn_flux"
bnb_4bit_compute_dtype = torch.float16
nf4_config = BitsAndBytesConfig(
load_in_4bit=True,
bnb_4bit_quant_type="nf4",
bnb_4bit_compute_dtype=bnb_4bit_compute_dtype,
)
pipeline = AutoPipelineForText2Image.from_pretrained(repo_id,
torch_dtype=bnb_4bit_compute_dtype
)
pipeline.enable_model_cpu_offload()
image = pipeline(
"Astronaut in a jungle, cold color palette, muted colors, detailed, 8k", num_inference_steps=28, guidance_scale=3.5, height=768
).images[0]
image
image = pipeline(
"Astronaut in a jungle, cold color palette, muted colors, detailed, 8k, yarn art style", num_inference_steps=28, guidance_scale=3.5, height=768
).images[0]
image

