Measure BERT model performance using WASM and WebGPU
Explore and manage STM32 ML models with the STM32AI Model Zoo dashboard
Text-To-Speech (TTS) Evaluation using objective metrics.
Convert a Stable Diffusion XL checkpoint to Diffusers and open a PR
View LLM Performance Leaderboard
View RL Benchmark Reports
Explore GenAI model efficiency on ML.ENERGY leaderboard
Calculate survival probability based on passenger details
Compare code model performance on benchmarks
Display benchmark results
Merge machine learning models using a YAML configuration file
Request model evaluation on COCO val 2017 dataset
Explore and submit models using the LLM Leaderboard
The WebGPU Embedding Benchmark is a tool designed to measure the performance of BERT models using WebAssembly (WASM) and WebGPU. It provides a platform to evaluate and compare the efficiency of embedding models across different hardware and software configurations. This benchmark is particularly useful for developers and researchers looking to optimize machine learning workloads in web-based environments.
What is the difference between WebGL and WebGPU?
WebGPU is the successor to WebGL, offering improved performance and better support for modern GPUs. WebGPU provides more efficient memory management and faster computation for machine learning tasks.
Which browsers support WebGPU?
As of now, WebGPU is supported in Chrome, Edge, and Safari Technology Preview. Ensure your browser is up-to-date to run the benchmark effectively.
How can I ensure consistent benchmark results?
To achieve consistent results, run the benchmark in a controlled environment with minimal background processes. Ensure the system's GPU is not under heavy load from other applications.