Instructions to use yanxg/FLUX.1-Kontext-dev-custom-B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use yanxg/FLUX.1-Kontext-dev-custom-B with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("yanxg/FLUX.1-Kontext-dev-custom-B", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
Upload model
Browse files- config.json +2 -2
- diffusion_pytorch_model.safetensors +1 -1
config.json
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"attention_head_dim": 64,
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"guidance_embeds": false,
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"in_channels": 64,
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"attention_head_dim": 64,
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"in_channels": 64,
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diffusion_pytorch_model.safetensors
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version https://git-lfs.github.com/spec/v1
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