Track can be with or without Gradio
and Track 2 you have to use Gradio
yes Track 1 is MCP and Track 2 is agents
Reuben fernandes PRO
Reubencf
AI & ML interests
LLM
Recent Activity
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about 8 hours ago
AI Energy Score v2: Refreshed Leaderboard, now with Reasoning 🧠
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2 days ago
We Got Claude to Fine-Tune an Open Source LLM
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4 days ago
Ministral 3
Organizations
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11 days ago
ポストをします
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11 days ago
@yuki-sui
track 1 can be anything.
Track 2 you have to strictly use Gradio
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11 days ago
No it is made using Next.js
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11 days ago
Thanks a lot @ash-98
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12 days ago
@John6666 @3ddelano @Sammy1611 @anupbhat What are your thoughts on this ?
Post
2395
Hey everyone! 👋
I am thrilled to present MCP-1st-Birthday/Reuben_OS my submission for the Hugging Face MCP 1st Birthday Hackathon (Creative Track).
ReubenOS is a virtual cloud-based operating system designed specifically to act as a backend for Claude Desktop via the Model Context Protocol (MCP). It gives Claude a persistent environment to work in!
✨ Key Features
* 📱 Flutter IDE: Claude can write Flutter code and I can view/execute the files directly in the ReubenOS dashboard.
* 🎵 AI Audio Studio: Integrated with ElevenLabs to generate songs and voiceovers from text prompts within Claude.
* 🔒 Secure File System: A passkey-protected file system (private & public folders) to store code, JSON, and documents.
* 🧠 Gemini Integration: Access Google's Gemini model directly inside the OS.
* 📝 Quiz Engine: Ask Claude to "Create a Python quiz," and it deploys a graded interactive quiz to the web instantly.
I am thrilled to present MCP-1st-Birthday/Reuben_OS my submission for the Hugging Face MCP 1st Birthday Hackathon (Creative Track).
ReubenOS is a virtual cloud-based operating system designed specifically to act as a backend for Claude Desktop via the Model Context Protocol (MCP). It gives Claude a persistent environment to work in!
✨ Key Features
* 📱 Flutter IDE: Claude can write Flutter code and I can view/execute the files directly in the ReubenOS dashboard.
* 🎵 AI Audio Studio: Integrated with ElevenLabs to generate songs and voiceovers from text prompts within Claude.
* 🔒 Secure File System: A passkey-protected file system (private & public folders) to store code, JSON, and documents.
* 🧠 Gemini Integration: Access Google's Gemini model directly inside the OS.
* 📝 Quiz Engine: Ask Claude to "Create a Python quiz," and it deploys a graded interactive quiz to the web instantly.
posted
an
update
12 days ago
Post
2395
Hey everyone! 👋
I am thrilled to present MCP-1st-Birthday/Reuben_OS my submission for the Hugging Face MCP 1st Birthday Hackathon (Creative Track).
ReubenOS is a virtual cloud-based operating system designed specifically to act as a backend for Claude Desktop via the Model Context Protocol (MCP). It gives Claude a persistent environment to work in!
✨ Key Features
* 📱 Flutter IDE: Claude can write Flutter code and I can view/execute the files directly in the ReubenOS dashboard.
* 🎵 AI Audio Studio: Integrated with ElevenLabs to generate songs and voiceovers from text prompts within Claude.
* 🔒 Secure File System: A passkey-protected file system (private & public folders) to store code, JSON, and documents.
* 🧠 Gemini Integration: Access Google's Gemini model directly inside the OS.
* 📝 Quiz Engine: Ask Claude to "Create a Python quiz," and it deploys a graded interactive quiz to the web instantly.
I am thrilled to present MCP-1st-Birthday/Reuben_OS my submission for the Hugging Face MCP 1st Birthday Hackathon (Creative Track).
ReubenOS is a virtual cloud-based operating system designed specifically to act as a backend for Claude Desktop via the Model Context Protocol (MCP). It gives Claude a persistent environment to work in!
✨ Key Features
* 📱 Flutter IDE: Claude can write Flutter code and I can view/execute the files directly in the ReubenOS dashboard.
* 🎵 AI Audio Studio: Integrated with ElevenLabs to generate songs and voiceovers from text prompts within Claude.
* 🔒 Secure File System: A passkey-protected file system (private & public folders) to store code, JSON, and documents.
* 🧠 Gemini Integration: Access Google's Gemini model directly inside the OS.
* 📝 Quiz Engine: Ask Claude to "Create a Python quiz," and it deploys a graded interactive quiz to the web instantly.
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mrmanna's
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14 days ago
Post
1363
𝗔𝗿𝗲 𝗬𝗼𝘂 𝗕𝘂𝗶𝗹𝗱𝗶𝗻𝗴 𝗮 𝗧𝗿𝘂𝗲 𝗞𝗻𝗼𝘄𝗹𝗲𝗱𝗴𝗲 𝗕𝗮𝘀𝗲 𝗼𝗿 𝗝𝘂𝘀𝘁 𝗮 𝗦𝗺𝗮𝗿𝘁 𝗦𝗲𝗮𝗿𝗰𝗵 𝗘𝗻𝗴𝗶𝗻𝗲?
𝘞𝘩𝘺 𝘢 𝘴𝘪𝘮𝘱𝘭𝘦 𝘥𝘰𝘮𝘢𝘪𝘯 𝘮𝘰𝘥𝘦𝘭 𝘥𝘰𝘦𝘴 𝘮𝘰𝘳𝘦 𝘧𝘰𝘳 𝘵𝘳𝘶𝘵𝘩 𝘵𝘩𝘢𝘯 𝘢𝘯𝘰𝘵𝘩𝘦𝘳 𝘳𝘰𝘶𝘯𝘥 𝘰𝘧 𝘵𝘰𝘱-𝘬 𝘵𝘶𝘯𝘪𝘯𝘨
ᴘᴜʙʟɪꜱʜᴇᴅ ᴏɴ ᴍᴇᴅɪᴜᴍ ɪɴ AI Advances | ɴᴏᴠ 22
Most “Knowledge bases” today are just vector indexes with a chat UI.
Without the LLM, they know nothing. With the LLM, every answer re-rents the same knowledge in tokens.
𝗞𝗲𝘆 𝘁𝗮𝗸𝗲𝗮𝘄𝗮𝘆𝘀:
- A vector store isn’t a knowledge base; it’s a smart memory. The “knowledge” lives in the model you keep paying to re-read your own documents.
- Without a model (entities + relationships), you lock in two long-term costs: high tokens per question and shallow answers per question.
- A lightweight knowledge model lets you store facts once, query them cheaply, and use the LLM only for judgment and language — not for rediscovering the same truths forever.
𝗙𝘂𝗹𝗹 𝗮𝗿𝘁𝗶𝗰𝗹𝗲 👉
https://ai.gopubby.com/are-you-building-a-true-knowledge-base-or-just-a-smart-search-engine-549922e29359?sk=b755b4c54ca77ab7b6b83189be81b689
𝘞𝘩𝘺 𝘢 𝘴𝘪𝘮𝘱𝘭𝘦 𝘥𝘰𝘮𝘢𝘪𝘯 𝘮𝘰𝘥𝘦𝘭 𝘥𝘰𝘦𝘴 𝘮𝘰𝘳𝘦 𝘧𝘰𝘳 𝘵𝘳𝘶𝘵𝘩 𝘵𝘩𝘢𝘯 𝘢𝘯𝘰𝘵𝘩𝘦𝘳 𝘳𝘰𝘶𝘯𝘥 𝘰𝘧 𝘵𝘰𝘱-𝘬 𝘵𝘶𝘯𝘪𝘯𝘨
ᴘᴜʙʟɪꜱʜᴇᴅ ᴏɴ ᴍᴇᴅɪᴜᴍ ɪɴ AI Advances | ɴᴏᴠ 22
Most “Knowledge bases” today are just vector indexes with a chat UI.
Without the LLM, they know nothing. With the LLM, every answer re-rents the same knowledge in tokens.
𝗞𝗲𝘆 𝘁𝗮𝗸𝗲𝗮𝘄𝗮𝘆𝘀:
- A vector store isn’t a knowledge base; it’s a smart memory. The “knowledge” lives in the model you keep paying to re-read your own documents.
- Without a model (entities + relationships), you lock in two long-term costs: high tokens per question and shallow answers per question.
- A lightweight knowledge model lets you store facts once, query them cheaply, and use the LLM only for judgment and language — not for rediscovering the same truths forever.
𝗙𝘂𝗹𝗹 𝗮𝗿𝘁𝗶𝗰𝗹𝗲 👉
https://ai.gopubby.com/are-you-building-a-true-knowledge-base-or-just-a-smart-search-engine-549922e29359?sk=b755b4c54ca77ab7b6b83189be81b689
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15 days ago
Post
5969
Trained a model for emotion-controllable TTS based on MiMo audio on LAION's dataset.
Still very early and does have an issue with hallucinating but results seem pretty good so far, given that it is very early into the training run.
Will probably kick off a new run later with some settings tweaked.
Put up a demo here: https://huggingface.co/spaces/mrfakename/EmoAct-MiMo
(Turn 🔊 on to hear audio samples)
Still very early and does have an issue with hallucinating but results seem pretty good so far, given that it is very early into the training run.
Will probably kick off a new run later with some settings tweaked.
Put up a demo here: https://huggingface.co/spaces/mrfakename/EmoAct-MiMo
(Turn 🔊 on to hear audio samples)
soon it will be on par with gemini 3
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about 2 months ago
Post
3590
Qwen3-VL-4B is incredibly easy to fine-tune!
We've trained the first DSE model based on this model, and it's already performing at the same level as Jina v4!
While Jina Embeddings v4 is built on Qwen2.5-VL-3B (which has a non-commercial license), our model is based on Qwen3-VL-4B and released under Apache 2.0—making it fully commercially permissive.
Check out our DSE model here:
racineai/QwenAmann-4B-dse
We've trained the first DSE model based on this model, and it's already performing at the same level as Jina v4!
While Jina Embeddings v4 is built on Qwen2.5-VL-3B (which has a non-commercial license), our model is based on Qwen3-VL-4B and released under Apache 2.0—making it fully commercially permissive.
Check out our DSE model here:
racineai/QwenAmann-4B-dse
reacted to
m-ric's
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about 2 months ago
Post
4877
STOP EVERYTHING NOW - we might finally have a radical architecture improvement over Transformers!!! 🚨
A lone scientist just proposed Tiny Recursive Model (TRM), and it is literally the most impressive model that I've seen this year.
➡️ Tiny Recursive Model is 7M parameters
➡️ On ARC-AGI, it beats flagship models like Gemini-2.5-pro
Consider how wild this is: Gemini-2.5-pro must be over 10,000x bigger
and had 1,000 as many authors 😂 (Alexia is alone on the paper)
What's this sorcery?
In short: it's a very tiny Transformers, but it loops over itself at two different frequencies, updating two latent variables: one for the proposed answer and one for the reasoning.
@AlexiaJM started from the paper Hierarchical Reasoning Model, published a few months ago, that already showed breakthrough improvement on AGI for its small size (27M)
Hierarchical Reasoning Model had introduced one main feature:
🔎 Deep supervision
In their model, one part (here one layer) would run at high frequency, and another would be lower frequency, running only every n steps.
They had used a recurrent architecture, where these layers would repeat many times ; but to make it work they had to do many approximations, including not fully backpropagating the loss through all layers.
Alexia studied what was useful and what wasn't, and cleaned the architecture as follows :
Why use a recurrent architecture, when you can just make it a loop?
➡️ She made the network recursive, looping over itself
Why use 2 latent variables ?
➡️ She provides a crystal clear explanation : the one that changes frequently is the reasoning, the one that changes at low frequency is the proposed answer.
➡️ She runs ablation studies to validate that 2 is indeed optimal.
This new setup is a much more elegant way to process reasoning than generating huge chains of tokens as all flagship models currently do.
This might be the breakthrough we've been awaiting for so long!
A lone scientist just proposed Tiny Recursive Model (TRM), and it is literally the most impressive model that I've seen this year.
➡️ Tiny Recursive Model is 7M parameters
➡️ On ARC-AGI, it beats flagship models like Gemini-2.5-pro
Consider how wild this is: Gemini-2.5-pro must be over 10,000x bigger
and had 1,000 as many authors 😂 (Alexia is alone on the paper)
What's this sorcery?
In short: it's a very tiny Transformers, but it loops over itself at two different frequencies, updating two latent variables: one for the proposed answer and one for the reasoning.
@AlexiaJM started from the paper Hierarchical Reasoning Model, published a few months ago, that already showed breakthrough improvement on AGI for its small size (27M)
Hierarchical Reasoning Model had introduced one main feature:
🔎 Deep supervision
In their model, one part (here one layer) would run at high frequency, and another would be lower frequency, running only every n steps.
They had used a recurrent architecture, where these layers would repeat many times ; but to make it work they had to do many approximations, including not fully backpropagating the loss through all layers.
Alexia studied what was useful and what wasn't, and cleaned the architecture as follows :
Why use a recurrent architecture, when you can just make it a loop?
➡️ She made the network recursive, looping over itself
Why use 2 latent variables ?
➡️ She provides a crystal clear explanation : the one that changes frequently is the reasoning, the one that changes at low frequency is the proposed answer.
➡️ She runs ablation studies to validate that 2 is indeed optimal.
This new setup is a much more elegant way to process reasoning than generating huge chains of tokens as all flagship models currently do.
This might be the breakthrough we've been awaiting for so long!
Post
4261
Introducing the Nano Banana Node Editor! 🍌
Now you can control and manipulate Nano Banana images with a powerful, intuitive node-based system. Explore the creative possibilities at: Reubencf/Nano_Banana_Editor
This version is clearer, more inviting, and emphasizes the creative potential of your tool.
Now you can control and manipulate Nano Banana images with a powerful, intuitive node-based system. Explore the creative possibilities at: Reubencf/Nano_Banana_Editor
This version is clearer, more inviting, and emphasizes the creative potential of your tool.
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3 months ago
The Editor Has Been Updated would love your feedback
@John6666
@Bansal123
@zhaoqiyong
@zkelo
@heyanabelle
Take care
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3 months ago
yes pressing the ❓ brings up the help menu.
