Instructions to use VHKE/becc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use VHKE/becc 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("VHKE/becc") prompt = "BECC box of beco product placed on a table --d 45" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
File size: 289 Bytes
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shuffle_caption = false
caption_extension = '.txt'
keep_tokens = 1
[[datasets]]
resolution = 512
batch_size = 1
keep_tokens = 1
[[datasets.subsets]]
image_dir = 'C:\Users\marko\Downloads\FLUXGYM\fluxgym\datasets\becc'
class_tokens = 'BECC'
num_repeats = 10 |