Display and explore model leaderboards and chat history
Generate Shark Tank India Analysis
"One-minute creation by AI Coding Autonomous Agent MOUSE"
Open LLM(CohereForAI/c4ai-command-r7b-12-2024) and RAG
fake news detection using distilbert trained on liar dataset
Analyze content to detect triggers
Compare AI models by voting on responses
Identify named entities in text
Encode and decode Hindi text using BPE
Generative Tasks Evaluation of Arabic LLMs
Demo emotion detection
Detect emotions in text sentences
A benchmark for open-source multi-dialect Arabic ASR models
The AI2 WildBench Leaderboard (V2) is a comprehensive tool designed for comparing and analyzing the performance of various AI models, particularly in the domain of text analysis. It provides a centralized platform where users can explore model leaderboards and review chat history to understand model capabilities and limitations better.
• Model Performance Tracking: Displays performance metrics of different models in a structured leaderboard format.
• Chat History Review: Allows users to examine previous conversations and interactions with models.
• Model Comparison: Enables side-by-side comparison of models based on specific tasks or datasets.
• Customizable Filters: Provides options to filter models based on accuracy, F1 score, or other performance criteria.
• Data Visualization: Includes charts and graphs to help users understand performance trends over time.
• Real-Time Updates: Offers the latest information on model performance as new data becomes available.
What models are included in the AI2 WildBench Leaderboard (V2)?
The leaderboard includes a variety of AI models focused on text analysis, including state-of-the-art models like GPT, T5, and other comparable architectures.
Can I submit my own model to the leaderboard?
Yes, the platform allows users to submit their models for evaluation. Visit the official documentation for submission guidelines.
What metrics are used to rank models on the leaderboard?
Models are primarily ranked based on accuracy, F1 score, and other task-specific metrics. These metrics are evaluated on standardized benchmarks to ensure fair comparison.