Instructions to use julientassy/fantasy-pixel-lora-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use julientassy/fantasy-pixel-lora-v2 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("julientassy/fantasy-pixel-lora-v2") prompt = "fntsy_pixel pixel art portrait of a footballer, dark slate background, 16-color palette" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
fantasy_pixel_lora_v2
Model trained with AI Toolkit by Ostris

- Prompt
- fntsy_pixel pixel art portrait of a footballer, dark slate background, 16-color palette
Trigger words
You should use fntsy_pixel to trigger the image generation.
Download model and use it with ComfyUI, AUTOMATIC1111, SD.Next, Invoke AI, etc.
Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.
Use it with the 🧨 diffusers library
from diffusers import AutoPipelineForText2Image
import torch
pipeline = AutoPipelineForText2Image.from_pretrained('black-forest-labs/FLUX.1-dev', torch_dtype=torch.bfloat16).to('cuda')
pipeline.load_lora_weights('julientassy/fantasy-pixel-lora-v2', weight_name='fantasy_pixel_lora_v2.safetensors')
image = pipeline('fntsy_pixel pixel art portrait of a footballer, dark slate background, 16-color palette').images[0]
image.save("my_image.png")
For more details, including weighting, merging and fusing LoRAs, check the documentation on loading LoRAs in diffusers
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Model tree for julientassy/fantasy-pixel-lora-v2
Base model
black-forest-labs/FLUX.1-dev