Instructions to use hjh3927/flux-fill-chart1-2-data-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use hjh3927/flux-fill-chart1-2-data-lora 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-Fill-dev", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("hjh3927/flux-fill-chart1-2-data-lora") prompt = "Three-panel image. [Left]: Full infographic with data elements and decorations. [Center]: Only data elements(bars, pie or annular sectors, lines, scatter points). [Right]: Only decorative elements(text labels, titles, icons, pictograms, arrows). Center and Right are complementary, together forming the Left." image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 28018649b6d8f4978dd30eac13961c3c012a4002d147af49fbda01aa16206292
- Size of remote file:
- 14.8 kB
- SHA256:
- 6c498cca10eda16a049e881fe06a3d2e75c3ba78bc3b1c425bdac3afcdb43733
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.