JonnaMat Automates Model Tracking with HuggingFace Slack App
A new Slack app brings Hugging Face model tracking directly into team workspaces. The tool sends real-time notifications about model milestones, download counts, and organization activity straight to Slack channels.
Developer JonnaMat created the app to automate celebration of 'small wins' that teams experience during AI development. Instead of manually sharing screenshots when models hit download milestones, teams can now receive automatic updates.
Tracking features for teams
- Subscribe to any Hugging Face model or organization for automatic updates.
- Receive milestone notifications at 100, 500, 1k, 10k, 50k downloads and beyond.
- Get alerts when organizations release new models or gain followers.
- Track competitor activity and download spikes before official announcements.
- Run on-demand stats with simple slash commands.
- Access weekly digest summaries every Friday.
Small agencies and development teams working on AI projects can stay informed without constantly checking the Hugging Face Hub. The tool also serves as a competitive intelligence resource, allowing users to monitor when other organizations release new models or experience sudden growth.
Developer notes and setup for HuggingFace Slack App
The app runs entirely through Slack Socket Mode, meaning no public URL or server exposure is required. This makes installation straightforward for teams with basic Python knowledge. Requirements include Python 3.9 or higher and standard Slack app permissions.
JonnaMat explained the motivation behind the project:
'I built this app to automate that celebration and turn static screenshots into a live, interactive 'playground.''
The developer notes that the tool preserves subscriptions across bot restarts using JSON file storage with thread-safe locking. Future updates are planned, including per-channel settings, leaderboard commands, and database backend options.
Get HuggingFace Slack App on GitHub or visit the project page for more details.