[inference providers] tutorial for image editing with inference providers #1880
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pcuenca
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Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
| # Initialize the client with fal-ai provider for fast image processing | ||
| client = InferenceClient( | ||
| provider="fal-ai", | ||
| api_key=os.environ["HF_TOKEN"], |
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if you export the HF_TOKEN above you don't need to explicitly pass the token. (in case you want to simplify the code a bit)
though probably better to be explicit.
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| </Tip> | ||
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| ## Step 1: Set Up Authentication |
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smol suggestion would be to add a TL;DR here with the link to a deployed space where people can try out the model directly and link to the code snippet below.
Co-authored-by: vb <vaibhavs10@gmail.com>
….com/huggingface/hub-docs into inference-providers-image-edit-guide
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I noticed https://huggingface.co/docs/inference-providers/en/guides/image-editor does not show any input or output images - would be great if you could add some, similar to https://docs.bfl.ai/guides/prompting_guide_kontext_i2i (which has plenty visual examples) |
| 1. **Accept image uploads** through a web interface | ||
| 2. **Process natural language prompts** editing instructions like "Turn the cat into a tiger" | ||
| 3. **Transform images** using Qwen Image Edit or FLUX.1 Kontext | ||
| 4. **Display results** in a Gradio interface |
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adding a screenshot of the end-result Gradio app would have been neat.
Other than that, cool tutorial!
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(or a screenshot of https://huggingface.co/spaces/Qwen/Qwen-Image-Edit)
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lol made a similar comment as @NielsRogge at the same time 🤯
This PR adds a guide on using Qwen Image Edit with inference providers.