Instructions to use callgg/kontext-decoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use callgg/kontext-decoder with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import load_image # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("callgg/kontext-decoder", dtype=torch.bfloat16, device_map="cuda") prompt = "Turn this cat into a dog" input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png") image = pipe(image=input_image, prompt=prompt).images[0] - Notebooks
- Google Colab
- Kaggle
Update transformer/config.json
Browse files- transformer/config.json +0 -1
transformer/config.json
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{
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"_class_name": "FluxTransformer2DModel",
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"_diffusers_version": "0.35.0.dev0",
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"_name_or_path": "./FLUX.1-Kontext-dev/transformer",
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"attention_head_dim": 128,
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"axes_dims_rope": [
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16,
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{
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"_class_name": "FluxTransformer2DModel",
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"_diffusers_version": "0.35.0.dev0",
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"attention_head_dim": 128,
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"axes_dims_rope": [
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16,
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