Instructions to use Jaytsh/FLUX-B2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Jaytsh/FLUX-B2 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", torch_dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Jaytsh/FLUX-B2") prompt = "-" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 51fe95b105c6a78feb47f85b3f75e00c6d7221e09501cadb3ab3161870a0bf02
- Size of remote file:
- 331 MB
- SHA256:
- 24778cf1f26a17997d9ee863dc8abb5a677919a6048fc4e4e9478452ee59e74e
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