Image-to-Image
Diffusers
Safetensors
Diffusion Single File
English
FluxKontextPipeline
image-generation
flux
Instructions to use AlekseyCalvin/Flux_Kontext_Dev_fp8_scaled_diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use AlekseyCalvin/Flux_Kontext_Dev_fp8_scaled_diffusers 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("AlekseyCalvin/Flux_Kontext_Dev_fp8_scaled_diffusers", 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] - Diffusion Single File
How to use AlekseyCalvin/Flux_Kontext_Dev_fp8_scaled_diffusers with Diffusion Single File:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
Update transformer/config.json
Browse files- transformer/config.json +1 -1
transformer/config.json
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{
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"_class_name": "FluxTransformer2DModel",
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"_diffusers_version": "0.
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"_name_or_path": "../checkpoints/flux-dev/transformer",
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"attention_head_dim": 128,
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"axes_dims_rope": [
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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": "../checkpoints/flux-dev/transformer",
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"attention_head_dim": 128,
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"axes_dims_rope": [
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