jaymueller multimodalart HF Staff commited on
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Correct safety filter (#7)

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- Update README.md (aebf2be7d6cdb3419c04f6d4631a4a9aa43708b5)


Co-authored-by: Apolinário from multimodal AI art <[email protected]>

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  1. README.md +17 -30
README.md CHANGED
@@ -36,6 +36,18 @@ Developers and creatives looking to build on top of `FLUX.1 Kontext [dev]` are e
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  `FLUX.1 Kontext [dev]` is also available in both [ComfyUI](https://github.com/comfyanonymous/ComfyUI) and [Diffusers](https://github.com/huggingface/diffusers).
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  ### Using with diffusers 🧨
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  ```shell
@@ -55,23 +67,9 @@ pipe.to("cuda")
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  input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png")
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  image = pipe(
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- image=input_image,
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- prompt="Add a hat to the cat",
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- guidance_scale=2.5,
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- ).images[0]
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- ```
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-
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- Text-to-image:
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- ```py
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- import torch
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- from diffusers import FluxKontextPipeline
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-
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- pipe = FluxKontextPipeline.from_pretrained("black-forest-labs/FLUX.1-Kontext-dev", torch_dtype=torch.bfloat16)
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- pipe.to("cuda")
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-
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- image = pipe(
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- prompt="A dog eating pizza",
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- guidance_scale=2.5,
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  ).images[0]
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  ```
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@@ -80,9 +78,9 @@ Flux Kontext comes with an integrity checker, which should be run after the imag
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  ```python
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  import torch
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  import numpy as np
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- from flux.safety import PixtralIntegrity
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- integrity_checker = PixtralIntegrity(torch.device("cuda"))
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  image_ = np.array(image) / 255.0
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  image_ = 2 * image_ - 1
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  image_ = torch.from_numpy(image_).to("cuda", dtype=torch.float32).unsqueeze(0).permute(0, 3, 1, 2)
@@ -92,17 +90,6 @@ raise ValueError("Your image has been flagged. Choose another prompt/image or tr
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  For VRAM saving measures and speed ups check out the [diffusers docs](https://huggingface.co/docs/diffusers/en/index)
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- ## API Endpoints
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- The FLUX.1 Kontext models are also available via API from the following sources
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- - bfl.ai: https://docs.bfl.ai/
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- - DataCrunch: https://datacrunch.io/flux-kontext
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- - fal: https://fal.ai/flux-kontext
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- - Replicate: https://replicate.com/blog/flux-kontext
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- - https://replicate.com/black-forest-labs/flux-kontext-dev
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- - https://replicate.com/black-forest-labs/flux-kontext-pro
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- - https://replicate.com/black-forest-labs/flux-kontext-max
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- - Runware: https://runware.ai/blog/introducing-flux1-kontext-instruction-based-image-editing-with-ai?utm_source=bfl
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- - TogetherAI: https://www.together.ai/models/flux-1-kontext-dev
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  ---
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  `FLUX.1 Kontext [dev]` is also available in both [ComfyUI](https://github.com/comfyanonymous/ComfyUI) and [Diffusers](https://github.com/huggingface/diffusers).
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+ ## API Endpoints
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+ The FLUX.1 Kontext models are also available via API from the following sources
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+ - bfl.ai: https://docs.bfl.ai/
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+ - DataCrunch: https://datacrunch.io/flux-kontext
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+ - fal: https://fal.ai/flux-kontext
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+ - Replicate: https://replicate.com/blog/flux-kontext
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+ - https://replicate.com/black-forest-labs/flux-kontext-dev
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+ - https://replicate.com/black-forest-labs/flux-kontext-pro
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+ - https://replicate.com/black-forest-labs/flux-kontext-max
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+ - Runware: https://runware.ai/blog/introducing-flux1-kontext-instruction-based-image-editing-with-ai?utm_source=bfl
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+ - TogetherAI: https://www.together.ai/models/flux-1-kontext-dev
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+
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  ### Using with diffusers 🧨
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  ```shell
 
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  input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png")
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  image = pipe(
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+ image=input_image,
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+ prompt="Add a hat to the cat",
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+ guidance_scale=2.5
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ).images[0]
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  ```
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  ```python
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  import torch
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  import numpy as np
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+ from flux.content_filters import PixtralContentFilter
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+ integrity_checker = PixtralContentFilter(torch.device("cuda"))
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  image_ = np.array(image) / 255.0
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  image_ = 2 * image_ - 1
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  image_ = torch.from_numpy(image_).to("cuda", dtype=torch.float32).unsqueeze(0).permute(0, 3, 1, 2)
 
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  For VRAM saving measures and speed ups check out the [diffusers docs](https://huggingface.co/docs/diffusers/en/index)
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  ---
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