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Abubakar Abid

abidlabs

https://abidlabs.github.io

AI & ML interests

self-supervised learning, applications to medicine & biology, interpretation, reproducibility

Recent Activity

reacted to RiverZ's post with 🔥 about 7 hours ago

🚀 Excited to Share Our Latest Work: In-Context Edit: Enabling Instructional Image Editing with In-Context Generation in Large Scale Diffusion Transformer～ 🎨 Daily Paper: In-Context Edit: Enabling Instructional Image Editing with In-Context Generation in Large Scale Diffusion Transformer (2504.20690) 🔓 Code is now open source! 🔥 Huggingface DEMO: RiverZ/ICEdit 🌐 Project Website: https://river-zhang.github.io/ICEdit-gh-pages/ 🏠 GitHub Repository: https://github.com/River-Zhang/ICEdit/blob/main/scripts/gradio_demo.py 🤗 Huggingface: sanaka87/ICEdit-MoE-LoRA 📄 arxiv Paper: In-Context Edit: Enabling Instructional Image Editing with In-Context Generation in Large Scale Diffusion Transformer (2504.20690) 🔥 Why it’s cool: - Achieves high-quality, multi-task image editing. - Uses only 1% of the training parameters and 0.1% of the training data compared to existing methods — extremely efficient - Beats several commercial models on background preservation, ID control, and consistency - Open-source, low-cost, faster, and stronger — think of it as the “DeepSeek of image editing” 👀 We also implemented a Gradio demo app, available directly in our GitHub repo! And we made a flashy demo video — happy to send it your way!

reacted to RiverZ's post with 🤗 about 7 hours ago

replied to their post 1 day ago

Hi folks! Excited to share a new feature from the Gradio team along with a tutorial. If you don't already know, Gradio is an open-source Python library used to build interfaces for machine learning models. Beyond just creating UIs, Gradio also exposes API capabilities and now, Gradio apps can be launched Model Context Protocol (MCP) servers for LLMs. If you already know how to use Gradio, there are only two additional things you need to do: * Add standard docstrings to your function (these will be used to generate the descriptions for your tools for the LLM) * Set `mcp_server=True` in `launch()` Here's a complete example (make sure you already have the latest version of Gradio installed): ```py import gradio as gr def letter_counter(word, letter): """Count the occurrences of a specific letter in a word. Args: word: The word or phrase to analyze letter: The letter to count occurrences of Returns: The number of times the letter appears in the word """ return word.lower().count(letter.lower()) demo = gr.Interface( fn=letter_counter, inputs=["text", "text"], outputs="number", title="Letter Counter", description="Count how many times a letter appears in a word" ) demo.launch(mcp_server=True) ``` This is a very simple example, but you can add the ability to generate Ghibli images or speak emotions to any LLM that supports MCP. Once you have an MCP running locally, you can copy-paste the same app to host it on [Hugging Face Spaces](https://huggingface.co/spaces/) as well. All free and open-source of course! Full tutorial: https://www.gradio.app/guides/building-mcp-server-with-gradio

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HOW TO ADD MCP SUPPORT TO ANY 🤗 SPACE

Gradio now supports MCP! If you want to convert an existing Space, like this one hexgrad/Kokoro-TTS, so that you can use it with Claude Desktop / Cursor / Cline / TinyAgents / or any LLM that supports MCP, here's all you need to do:

1. Duplicate the Space (in the Settings Tab)
2. Upgrade the Gradio sdk_version to 5.28 (in the README.md)
3. Set mcp_server=True in launch()
4. (Optionally) add docstrings to the function so that the LLM knows how to use it, like this:

def generate(text, speed=1):
    """
    Convert text to speech audio.

    Parameters:
        text (str): The input text to be converted to speech.
        speed (float, optional): Playback speed of the generated speech.