Future AGI
OSSFuture AGI is an open-source platform designed for engineering and optimizing AI agents, integrating tools for trac…
Comparable Evaluation and Monitoring AI agents, ranked by popularity. Not sold on Speech-to-Text Benchmark? These are the closest options worth a look.
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Speech-to-Text Benchmark is an open-source framework designed to evaluate and compare the performance of different speech-to-text (STT) engines. It provides a standardized way to measure accuracy, latency, and other metrics across various STT solutions. The tool is minimalist and extensible, allowing users to integrate custom datasets or engines.
Future AGI is an open-source platform designed for engineering and optimizing AI agents, integrating tools for trac…
Inspect is an open-source framework designed for evaluating large language models (LLMs), providing tools to assess…
JiWER is a Python library designed to compute Word Error Rate (WER) and other speech recognition accuracy metrics e…
Laminar is an open-source platform designed to trace, evaluate, label, and analyze large language model (LLM) data …
LangTest is an open-source toolkit designed for evaluating and monitoring the performance of natural language proce…
The Language Model Evaluation Harness is a standardized framework for evaluating the performance of generative lang…
LLMPerf is a benchmarking tool designed to measure and compare the performance of large language model (LLM) APIs, …
lmms-eval is an open-source evaluation framework designed for consistent and efficient assessment of Large Multimod…
Massive Text Embedding Benchmark (MTEB) is a standardized evaluation framework that measures the performance of tex…
Melting Pot is a suite of customizable test scenarios designed for evaluating multi-agent reinforcement learning (M…
Meta-World is an open-source benchmark environment designed for evaluating meta-reinforcement learning and multi-ta…
mir_eval is a Python library designed for evaluating Music Information Retrieval (MIR) systems by providing standar…