Measure BERT model performance using WASM and WebGPU
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Persian Text Embedding Benchmark
Benchmark AI models by comparison
View LLM Performance Leaderboard
Convert a Stable Diffusion XL checkpoint to Diffusers and open a PR
Submit deepfake detection models for evaluation
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Evaluate code generation with diverse feedback types
Browse and filter ML model leaderboard data
Launch web-based model application
Measure execution times of BERT models using WebGPU and WASM
Browse and submit LLM evaluations
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.