opov VS benchmark

Compare opov vs benchmark and see what are their differences.

opov

Operator Overloading for Typescript with Tagged Template Literals (by crubier)

benchmark

TorchBench is a collection of open source benchmarks used to evaluate PyTorch performance. (by pytorch)
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opov benchmark
1 3
11 789
- 3.3%
3.3 9.8
12 months ago 2 days ago
JavaScript Python
- BSD 3-clause "New" or "Revised" License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

opov

Posts with mentions or reviews of opov. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-05-19.

benchmark

Posts with mentions or reviews of benchmark. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-05-19.

What are some alternatives?

When comparing opov and benchmark you can also consider the following projects:

requests-wasm-polyfill - Drop-in replacement for the requests library for wasm python

llama.cpp - LLM inference in C/C++

potatogpt - Pure Typescript, dependency free, ridiculously slow implementation of GPT2 for educational purposes

wonnx - A WebGPU-accelerated ONNX inference run-time written 100% in Rust, ready for native and the web

onnxruntime - ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator

transformers - 🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.

shumai - Fast Differentiable Tensor Library in JavaScript and TypeScript with Bun + Flashlight

tfjs - A WebGL accelerated JavaScript library for training and deploying ML models.