Hugging Face's logo
Activity Feed

AI & ML interests

None defined yet.

Recent Activity
Prabhjotschugh  authored a paper 3 days ago
Not Truly Multilingual: Script Consistency as a Missing Dimension in VLM Evaluation
Prabhjotschugh  authored a paper 3 days ago
FirstPass: Grounding AI Scientific Judgment in Multi-Round Editorial Outcomes
Prabhjotschugh  authored a paper 3 days ago
Beyond 'One Language, One Script': Quantifying Orthographic Bias in Multilingual VLMs with PuMVR
View all activity
fffiloni 
posted an update about 21 hours ago
view post
Post
135
⏱️ Built a small Space for Visual Chronometer / Pulse of Motion.

Upload a video and estimate its Physical FPS: the frame rate implied by visual motion, independent of metadata.
Useful to inspect “chronometric hallucination” in generated videos: clips that look smooth, but move with the wrong physical time scale.

Try it here: fffiloni/Pulse-of-Motion
Prabhjotschugh 
authored 4 papers 3 days ago
fffiloni 
posted an update 6 days ago
view post
Post
1509
A few weeks ago, @victor opened the door: coding agents can now ship Hugging Face Spaces autonomously.

I pulled on that thread.

As someone who builds and ships Gradio demos regularly, I didn’t just want to reproduce the loop. I wanted to see what happens when that loop is plugged into the whole Hugging Face stack.

The interesting part is not only that an agent can ship a Space.

It’s what happens when Space generation becomes a first-class Hugging Face workflow.

That became Agentic Space Factory.

More soon. 🤗
  • 1 reply
·
Abhaykoul 
posted an update 16 days ago
view post
Post
234
Shipped v0.1.2 of vtx — a minimalist coding agent for the terminal.

Most agentic CLIs ship 10k+ token system prompts. Vtx is ~2,200. Less prompt overhead means more room for your code in the model's context window.

Vtx is a from-scratch Python implementation of the design philosophy behind pi-mono — same principles, pure Python, no transpiled runtime.

What ships out of the box:

→ Textual TUI + headless CLI (vtx -p "fix the failing test")
→ 49 LLM provider gateways, all declared in a single provider.yaml
→ 5 core tools (read / edit / write / bash / find) plus web search and fetch
→ Session tree with compaction, handoff, and resume
→ AGENTS.md / CLAUDE.md auto-discovery
→ Skills system — drop SKILL.md files in .agents/skills/ and they become slash commands
→ Two OAuth flows (GitHub Copilot device flow, OpenAI Codex PKCE)
→ Two-mode permissions: prompt (default) or auto, with a safe-command allowlist

This release adds a proper extension system. Register new LLM-callable tools, intercept tool calls, hook lifecycle events, and add slash commands from a single register(api) function in a Python file under ~/.vtx/agent/extensions/. Extensions can override built-in tools by name and chain handler logic across subscribers.

Apache 2.0. uv tool install vtx-coding-agent and you're running.

GitHub: https://github.com/OEvortex/vtx-coding-agent
PyPI: https://pypi.org/project/vtx-coding-agent

Built in the open. Feedback, extensions, and PRs welcome.
DongfuJiang 
authored 3 papers 27 days ago
alielfilali01 
posted an update about 1 month ago
view post
Post
573
Plans in HTML > Plans in Markdown
johko 
posted an update about 1 month ago
view post
Post
148
One prompt, three answers - which model is from where?

johko/llm-blind-date

I built a little demo where you give three models (Apertus, Llama, Qwen3) the same prompt and in the end you have to guess which is which just based on their answers.

GIve it a try! ;)
fffiloni 
posted an update about 2 months ago
view post
Post
3843
I built HF Radio on Hugging Face Spaces 📻
fffiloni/HF-Radio

A live community radio for AI-generated songs, powered by tracks created with ACE-Step.

You can tune in, discover community-made songs in many languages, vote on what sounds good, and mark your real favorites as Bangers.

The more people listen, vote, and create, the better the station gets.

Under the hood, it connects a few Hugging Face pieces together:

Spaces for the live app, HF buckets for community tracks, OAuth for signed-in listeners, server-side streaming with ffmpeg, hourly playlist refreshes, moderation, jingles, and community feedback loops.

It’s not just a playlist.

It’s a shared taste experiment:
new songs get a shot every hour, and the community helps decide what deserves another spin.

Come listen.
Find weird gems.
Support the Bangers.
Shape the radio.

—> fffiloni/HF-Radio
Tonic 
posted an update about 2 months ago
view post
Post
2992
🙋🏻‍♂️ Hey there folks ,

Turns out : if we predict 🌏 earth we can save a lot of time looking for interesting things and less time looking at things that we expect to see.

Sentinel-2 imagery 🛰️basically takes a long time to download towards earth. so our "near real time" systems are quite far from that in practical terms.

meanwhile , if we "predict" what we will see , based on what we do see , we can send down much less data in a timely way , and prioritize 📡earth-bound response .

I'm talking about illegal fishing , logging , mining or building in nature reserves , the more of that we predict early the more we're able to stop it on time.

At least that's the concept !

check out the blog : https://huggingface.co/blog/Tonic/save-patagonia-by-predicting-earth


- Collection: https://huggingface.co/collections/NuTonic/earth-observation-with-temporal-and-general-understanding
- Code: https://github.com/Josephrp/Nutonic
- Dataset: NuTonic/sat-vl-sft-training-ready-v1
- Model: NuTonic/lspace
- Training: NuTonic/lspace-trackio
- Evals: NuTonic/Patagonia_Eval
  • 2 replies
·
DongfuJiang 
authored 4 papers about 2 months ago
fffiloni 
posted an update about 2 months ago
view post
Post
505
Great technical guide by Nico Martin on the Hugging Face blog, showing how to use Transformers.js inside a Chrome extension and run ONNX models from the Hub locally with WebGPU inside a Manifest V3 extension.

The interesting part: this is not just a chatbot in a side panel.

The article walks through the architecture behind a browser agent that can read open tabs, query webpages, search history, and highlight elements directly on the page — with models downloaded from the Hugging Face Hub, cached under the extension origin, and executed locally instead of being called through a remote API for every prompt.

A strong blueprint for building local-first web copilots, reading assistants, and AI-powered browsing workflows.

Article: https://huggingface.co/blog/transformersjs-chrome-extension
fffiloni 
posted an update about 2 months ago
view post
Post
346
I’ve been reading “What if AI systems weren’t chatbots?”
What if AI systems weren't chatbots? (2605.07896) 👀

The paper asks a simple but important question: what if the chatbot interface is not just a neutral wrapper around AI models, but part of the problem?

A chatbot can make a system feel more capable, more certain, and more “human” than it really is. That matters, because interfaces shape how we trust, use, and delegate to AI systems.

When everything becomes: ask → answer
we can lose sight of the actual workflow:
- parameters
- alternatives
- uncertainty
- intermediate steps
- failure modes
- human control

For creative AI especially — image, video, editing, animation — I’m not sure “chat” should always be the default interface.

Sometimes we need a conversation.
But often we need a canvas, a timeline, sliders, masks, previews, comparisons, and visible pipelines.

This is also why I find many open ML demos interesting: Spaces, Gradio apps, visual tools, small focused interfaces.

They often explore another direction — not just better assistants, but better tools. 🤗
  • 2 replies
·