# HuggingFace Projects at AI Tinkerers

> Canonical HTML: https://aitinkerers.org/technologies/huggingface
> Markdown URL: https://aitinkerers.org/technologies/huggingface.md
> Technology record last updated: 2026-02-23T20:56:58Z
> Generated: 2026-09-22T10:43:11Z

The central hub for the AI community: providing over 150,000 models, 30,000 datasets, and collaborative machine learning tooling.

Hugging Face is the leading collaboration platform: it advances and democratizes artificial intelligence through open source and open science. The Hugging Face Hub hosts a massive repository where the ML community shares and deploys over 150,000 models and 30,000 datasets. Core tooling includes the widely adopted Transformers library, which provides a unified API for state-of-the-art models (like BERT, GPT, and T5) across NLP, computer vision, and audio tasks. Developers leverage this ecosystem (including libraries like Diffusers and Datasets) to train, fine-tune, and deploy production-ready AI applications with minimal effort and cost.

- Official technology site: https://huggingface.co
- Public AI Tinkerers demos and talks: 7
- Result page: 1 of 1

## Recent Public Talks and Demos

### [\[UofT\] Print Anything: Building the Pipeline from Natural Language to 3D Object](https://toronto.aitinkerers.org/talks/rsvp_z0pA85I3o0k)

What if you could 3D print something simply by describing it in plain English, just as you ask ChatGPT a question? That is the idea behind our project. Our system fine-tunes a Qwen 3 model with LoRA in Google Colab to generate ImplicitCAD code from natural language prompts. The generated code is then compiled into STL files, which can be used for 3D printing. ImplicitCAD is a code-based CAD tool, similar to OpenSCAD. Many people in the 3D printing community like it because script-based design allows precise and reproducible measurements. However, the downside is that users need to know how to write code. To address this, we built a two-phase training pipeline. In the first phase, the model learns ImplicitCAD syntax using real examples collected and filtered from the Thingiverse dataset on HuggingFace. This helps the model understand how 3D geometry is written in code. In the second phase, we introduce logical and spatial reasoning problems so the model can go beyond simple pattern matching. In addition to the model, we also built a web-based preview environment and a Dockerized version of ImplicitCAD. This removes the usual edit-compile-wait workflow that makes these tools difficult to use. The project is meant to be a starting point that future teams can build on and extend.

- Event context: AI Tinkerers Toronto - March - hosted by Mozilla! — 2026-03-25 — Toronto
- Public talk page: https://toronto.aitinkerers.org/talks/rsvp_z0pA85I3o0k

### [Meet Reachy: Bringing AI Agents and Robots to Life](https://montreal.aitinkerers.org/talks/rsvp_W5uswbok9N0)

Reachy Mini is a voice-enabled and vision-capable AI robot that can see, speak, remember, reason through graph-based orchestration, use Databricks, and control a computer or external tools in real time.

- Event context: AI Tinkerers Montreal - March Demo Night — 2026-03-24 — Montreal
- Public talk page: https://montreal.aitinkerers.org/talks/rsvp_W5uswbok9N0

### [The Geometry of Identity: High-Performance Matching with LightGlue](https://hong-kong.aitinkerers.org/talks/rsvp_CKcqvusIVsI)

In this deep dive, we move beyond the "black box" of face detection to dissect the underlying logic of neural feature matching. While traditional biometric systems often rely on global embeddings, this session explores the mechanics of sparse feature matching and how it can be used to quantify similarity with sub-millisecond precision. We will focus on the end-to-end pipeline: starting with classical keypoint extraction using SIFT, followed by state-of-the-art neural matching via LightGlue. We will explore how LightGlue’s transformer-based architecture utilises attention mechanisms to adaptively match SIFT keypoints. Furthermore, we will discuss how these complex models are optimised for real-time edge inference—a critical requirement for modern robotics and spatial computing. I will showcase two real-world implementation examples, including an interactive Google Colab notebook, so please bring your laptops.

- Event context: AI Tinkerers Hong Kong: Deep Dive Series - Deep Dive featuring Spatial Computing and Robotics — 2026-02-05 — Hong Kong
- Public talk page: https://hong-kong.aitinkerers.org/talks/rsvp_CKcqvusIVsI

### [Cost-Effective Real-Time Voice AI for Robotics](https://waterloo.aitinkerers.org/talks/rsvp_3YU21hFfQYg)

Live demo of a working conversational robot (Reachy Mini) using ElevenLabs AI instead of gpt-realtime, while demonstrating the cost-prohibitive reality of real-time voice models of today I'll demonstrate: - The robot having natural voice conversations in real-time (small physical robot will be present) - How I integrated ElevenLabs Conversational AI with Reachy Mini hardware - Why ElevenLabs is dramatically cheaper than OpenAI's realtime API for applications - Head movement synchronization with speech audio (limited) This is a working open-source app on HuggingFace that anyone can install. I'll show the live robot, explain the architecture, and discuss the practical integration decisions that made it work.

- Event context: AI Tinkerers Waterloo – January Meetup — 2026-01-28 — Waterloo
- Public talk page: https://waterloo.aitinkerers.org/talks/rsvp_3YU21hFfQYg

### [tbai – A mini HuggingFace for robots](https://prague.aitinkerers.org/talks/rsvp_xTawThFvvEk)

With tbai, your quadruped or even bipedal robot will be walking in under ten minutes. What is tbai, and how did it become the backbone for legged robot research in Europe, Asia, and the USA? That is exactly what I will cover in this talk.

- Event context: AI Tinkerers Prague: Annual Christmas Meetup 2025 — 2025-12-16 — Prague
- Public talk page: https://prague.aitinkerers.org/talks/rsvp_xTawThFvvEk

### [PitchCraft AI](https://seattle.aitinkerers.org/talks/rsvp_z-OyH0yDpgs)

A set of investment banking relevant LLM agents (research, financial modeling, Associate, VP, etc.) that work together to create a sell side pitchbook. The primary benefit is reduction of iteration cycles required to get to 1) a high quality first draft and 2) final pitchbook to be presented to potential buyers.

- Event context: AI Tinkerers Seattle – June Meetup — 2025-06-28 — Seattle
- Public talk page: https://seattle.aitinkerers.org/talks/rsvp_z-OyH0yDpgs

### [from LLMs to reasoning models](https://quito.aitinkerers.org/talks/rsvp_5DTY9GNbFvw)

implementations of how to go from LLMs to reasoning models, by scaling inference time compute on open source models. Implementing techniques like Monte Carlo tree search, GRPO and beam search.

- Event context: AI Tinkerers - Quito Primer Meetup (Abril) — 2025-04-24 — Quito
- Public talk page: https://quito.aitinkerers.org/talks/rsvp_5DTY9GNbFvw

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