Browse and submit LLM evaluations
Find recent high-liked Hugging Face models
Convert and upload model files for Stable Diffusion
Convert Hugging Face model repo to Safetensors
Evaluate AI-generated results for accuracy
Multilingual Text Embedding Model Pruner
Display genomic embedding leaderboard
Push a ML model to Hugging Face Hub
Merge Lora adapters with a base model
Quantize a model for faster inference
Benchmark AI models by comparison
View RL Benchmark Reports
Convert PyTorch models to waifu2x-ios format
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.