Instructions to use fyp1/pattern_generation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use fyp1/pattern_generation 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("fyp1/pattern_generation") prompt = "A Kashmiri shawl-inspired pattern featuring delicate swirls of vines and paisleys in soft pastel shades, woven into an intricate border design for a light, airy, and elegant fabric." image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
File size: 631 Bytes
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tags:
- text-to-image
- lora
- diffusers
- template:diffusion-lora
widget:
- text: >-
A Kashmiri shawl-inspired pattern featuring delicate swirls of vines and
paisleys in soft pastel shades, woven into an intricate border
design for a light, airy, and elegant fabric.
output:
url: images/1727560066052__000001000_7.jpg
base_model: black-forest-labs/FLUX.1-dev
instance_prompt: null
---
# pattern_generation
<Gallery />
## Download model
Weights for this model are available in Safetensors format.
[Download](/fyp1/pattern_generation/tree/main) them in the Files & versions tab.
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