Display and filter leaderboard models
Multilingual Text Embedding Model Pruner
Evaluate adversarial robustness using generative models
View and submit LLM benchmark evaluations
Display benchmark results
Find and download models from Hugging Face
Create and upload a Hugging Face model card
Compare code model performance on benchmarks
Merge Lora adapters with a base model
Measure over-refusal in LLMs using OR-Bench
View NSQL Scores for Models
Calculate memory needed to train AI models
Optimize and train foundation models using IBM's FMS
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.