Browse and submit LLM evaluations
Upload a machine learning model to Hugging Face Hub
Persian Text Embedding Benchmark
Explore and benchmark visual document retrieval models
Compare audio representation models using benchmark results
Load AI models and prepare your space
Pergel: A Unified Benchmark for Evaluating Turkish LLMs
Browse and filter machine learning models by category and modality
Evaluate and submit AI model results for Frugal AI Challenge
Merge Lora adapters with a base model
Visualize model performance on function calling tasks
Benchmark models using PyTorch and OpenVINO
Track, rank and evaluate open LLMs and chatbots
The Open Tw Llm Leaderboard is a platform designed for model benchmarking, specifically for Large Language Models (LLMs). It serves as a centralized hub where users can browse and submit evaluations of different LLMs. The tool provides a comparative analysis of various models, highlighting their strengths and weaknesses. This leaderboard is particularly useful for researchers, developers, and enthusiasts looking to understand the performance of different LLMs across various tasks and datasets.
What is the purpose of Open Tw Llm Leaderboard? The purpose is to provide a centralized platform for comparing and analyzing the performance of different Large Language Models.
How do I submit an evaluation to the leaderboard? Submissions can be made by following the guidelines provided on the platform, typically involving providing detailed metrics and results from your evaluation.
Do I need to register to use the leaderboard? No, browsing the leaderboard is generally accessible without registration. However, submitting an evaluation may require creating an account.