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How to use Polycruz9/pixelo-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("fill-in-base-model", dtype=torch.bfloat16, device_map="cuda")
pipe.load_lora_weights("Polycruz9/pixelo-flux")
prompt = "better pixel, A pixelated image of a blue man and a white dog on a pink background made up of small square tiles. The blue mans head is on the left side of the image, while the white dog is to the right of the blue man. Both of the dogs are facing each other. The dogs mouth is slightly open, and the dogs tongue is sticking out of its mouth. The pink tiles are arranged in a grid pattern."
image = pipe(prompt).images[0]
______ ______ __ __ __ ______ ______ __ __ ______ __ ______
/\ == \/\ __ \ /\ \ /\ \_\ \ /\ ___\ /\ == \ /\ \/\ \ /\___ \ /\ \ /\ __ \
\ \ _-/\ \ \/\ \\ \ \____\ \____ \\ \ \____\ \ __< \ \ \_\ \\/_/ /__ \ \ \\ \ \/\ \
\ \_\ \ \_____\\ \_____\\/\_____\\ \_____\\ \_\ \_\\ \_____\ /\_____\ \ \_\\ \_____\
\/_/ \/_____/ \/_____/ \/_____/ \/_____/ \/_/ /_/ \/_____/ \/_____/ \/_/ \/_____/



Image Processing Parameters
| Parameter | Value | Parameter | Value |
|---|---|---|---|
| LR Scheduler | constant | Noise Offset | 0.03 |
| Optimizer | AdamW | Multires Noise Discount | 0.1 |
| Network Dim | 64 | Multires Noise Iterations | 10 |
| Network Alpha | 32 | Repeat & Steps | 20 & 2600 |
| Epoch | 14 | Save Every N Epochs | 1 |
Labeling: florence2-en(natural language & English)
Total Images Used for Training : 24
| Dimensions | Aspect Ratio | Recommendation |
|---|---|---|
| 1280 x 832 | 3:2 | Best |
| 1024 x 1024 | 1:1 | Default |
import torch
from pipelines import DiffusionPipeline
base_model = "black-forest-labs/FLUX.1-dev"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "Polycruz9/pixelo-flux"
trigger_word = "better pixel"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)
You should use better pixel to trigger the image generation.
Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.