Measure BERT model performance using WASM and WebGPU
Convert PaddleOCR models to ONNX format
Visualize model performance on function calling tasks
Merge machine learning models using a YAML configuration file
View RL Benchmark Reports
Create and manage ML pipelines with ZenML Dashboard
Explore and manage STM32 ML models with the STM32AI Model Zoo dashboard
Display and filter leaderboard models
Evaluate reward models for math reasoning
Upload a machine learning model to Hugging Face Hub
Browse and filter ML model leaderboard data
Measure over-refusal in LLMs using OR-Bench
Benchmark AI models by comparison
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.