In this exciting demonstration, we explore how you can enhance your productivity with cutting-edge features right at your fingertips. Experience seamless speech recognition and automatic text correction on GNU/Linux systems using just a couple of mouse clicks!
Speech Recognition: Activate by pressing *Mouse Button 9*. Say goodbye to typing fatigue as our system effortlessly converts spoken words into digital text.
Automatic LLM Text Correction: Press Mouse Button 8 for instant, intelligent corrections. Our advanced language model ensures your writing is polished and precise.
Whether you're a developer looking to streamline coding or someone who spends hours typing reports, this demonstration will show how these features can transform the way you work.
Don't miss out on discovering an innovative approach that integrates speech recognition and text correction into your daily routine with ease!
π¬ Drop a comment below if you have questions or want to share how these features could benefit your workflow.
π PawMatchAI Update: Smarter Visualization with Radar Charts! πΎ
Iβve just added a new feature to the project that bridges the gap between breed recognition and real world decision-making: π Radar charts for lifestyle-based breed insights.
π― Why This Matters Choosing the right dog isnβt just about knowing the breed , itβs about how that breed fits into your lifestyle.
To make this intuitive, each breed now comes with a six-dimensional radar chart that reflects: - Space Requirements - Exercise Needs - Grooming Level - Owner Experience - Health Considerations - Noise Behavior
Users can also compare two breeds side-by-side using radar and bar charts β perfect for making thoughtful, informed choices.
π‘ Whatβs Behind It? All visualizations are directly powered by the same internal database used by the recommendation engine, ensuring consistent, explainable results.
πΆ Try It Out Whether you're a first-time dog owner or a seasoned canine lover, this update makes it easier than ever to match with your ideal companion.
Yesterday we published the first large evaluation of the new model, showing that it absolutely leaves the competition in the dust. We have now made the results and data available here! Please check it out and β€οΈ !
reacted to clem's
post with π€ππ5 days ago
Open source models are immutable, this is a big pain.
When you open source a piece of software, users leave their feedbacks via issues or PRs. You can merge their feedbacks in semi real time, this creates a positive cycle. Then you have a community.
LLMs don't have these nice micro steps. There are no hot fixes. Even a minor version bump is an endeavor. I'm quite confident my model is being used by teams somewhere. But until next launch, it's awfully quiet.
I don't know the solution. Just a regular lament before weekend. π€
3 replies
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reacted to ritvik77's
post with ππ5 days ago
One feature Hugging Face could really benefit from is a contribution heatmap β a visual dashboard to track user engagement and contributions across models, datasets, and models over the year, similar to GitHubβs contribution graph. Guess what, Clem Delangue mentioned idea about using HF API reference for it and we made it for use.
If you are a Hugging Face user add this Space in your collection and it will give you all stats about your contributions and commits nearly same as GitHub. It's still a prototype and still working on it as a product feature.
Very interesting security section by @yjernite@lvwerra@reach-vb@dvilasuero & the team replicating R1. Broadly applicable to most open-source models & some to APIs (but APIs have a lot more additional risks because you're not in control of the underlying system):
Contributor Activity Tracking: Visualize yearly and monthly contributions through interactive calendars Top 100 Rankings: Provide rankings based on models, spaces, and dataset contributions Detailed Analysis: Analyze user-specific contribution patterns and influence Visualization: Understand contribution activities at a glance through intuitive charts and graphs
π Core Visualization Elements
Contribution Calendar: Track activity patterns with GitHub-style heatmaps Radar Chart: Visualize balance between models, spaces, datasets, and activity levels Monthly Activity Graph: Identify most active months and patterns Distribution Pie Chart: Analyze proportion by contribution type
π Ranking System
Rankings based on overall contributions, spaces, and models Automatic badges for top 10, 30, and 100 contributors Ranking visualization to understand your position in the community
π‘ How to Use
Select a username from the sidebar or enter directly Choose a year to view specific period activities Select desired items from models, datasets, and spaces View comprehensive contribution activities in the detailed dashboard
π Expected Benefits
Provide transparency for Hugging Face community contributors' activities Motivate contributions and energize the community Recognize and reward active contributors Visualize contributions to the open AI ecosystem
