Display and filter leaderboard models
Evaluate RAG systems with visual analytics
Measure over-refusal in LLMs using OR-Bench
Create and upload a Hugging Face model card
Merge machine learning models using a YAML configuration file
Upload a machine learning model to Hugging Face Hub
Convert and upload model files for Stable Diffusion
Find recent high-liked Hugging Face models
Load AI models and prepare your space
Evaluate reward models for math reasoning
Run benchmarks on prediction models
Push a ML model to Hugging Face Hub
Leaderboard of information retrieval models in French
Encodechka Leaderboard is a tool designed for model benchmarking, allowing users to compare and evaluate different AI models based on their performance metrics. It provides a centralized platform to display and filter leaderboard models, making it easier to identify top-performing models and understand their strengths.
• Model Comparison: Easily compare performance metrics of different AI models. • Filtering Options: Filter models based on specific criteria such as dataset, task, or model type. • Real-Time Updates: Stay up-to-date with the latest models and their performance. • Detailed Insights: Access in-depth information about each model's capabilities and benchmarks. • Customizable Views: Tailor the leaderboard to focus on metrics that matter most to your use case.
What models are included in the Encodechka Leaderboard?
The leaderboard features a wide range of AI models, including state-of-the-art models from leading research institutions and organizations.
How often is the leaderboard updated?
The leaderboard is updated in real-time to reflect the latest additions and performance changes in the AI model landscape.
Can I customize the metrics displayed on the leaderboard?
Yes, users can customize the view to focus on specific metrics such as accuracy, inference speed, or memory usage.