Instructions to use borisf/bbdec with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use borisf/bbdec 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("borisf/bbdec") prompt = "BBDec" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download dataset.toml from borisf/bbdec: direct link, hf CLI and curl.
- Browser
- Download file 250 Bytes
-
https://huggingface.co/borisf/bbdec/resolve/main/dataset.toml
- Command line
-
hf download hf://borisf/bbdec/dataset.toml
-
curl -L -o dataset.toml https://huggingface.co/borisf/bbdec/resolve/main/dataset.toml
250 Bytes
| [general] | |
| shuffle_caption = false | |
| caption_extension = '.txt' | |
| keep_tokens = 1 | |
| [[datasets]] | |
| resolution = 512 | |
| batch_size = 1 | |
| keep_tokens = 1 | |
| [[datasets.subsets]] | |
| image_dir = '/app/fluxgym/datasets/bbdec' | |
| class_tokens = 'BBDec' | |
| num_repeats = 10 |