Dev tools · alternatives · 2026
24 alternatives to KeraSH, a ML Framework in Shell
World's leading ML framework in shell. Contribute to MightyGoldenOctopus/KeraSH development by creating an account on GitHub.
KeraSH is a machine learning framework implemented in shell script, launched in 2019. It enables developers to build and run ML models using shell commands rather than traditional programming languages. The framework… Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes. KeraSH, a ML Framework in Shell launched in 2019; newer entries below may have overtaken it.
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TensorFlow 1.0▲823Open-source machine learning library by Google
2017 · tensorflow.org · its alternatives →
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a delightful machine learning tool that allows you to train, test, and use models without writing code - nidhaloff/igel
2020 · github.com · its alternatives →
- 4HP
2018 · scss.tcd.ie · its alternatives →
- 5CR
The goal of Carton is to let you use a single interface to run any machine learning model from any programming language. It’s currently difficult to integrate models that use different technologies (e.g. TensorRT, Ludwig, TorchScript, JAX, GGML, etc) into your application, especially if you’re not using Python. Even if you learn the details of integrating each of these frameworks, running multiple frameworks in one process can cause hard-to-debug crashes. Ideally, the ML framework a model was developed in should just be an implementation detail. Carton lets you decouple your application from…
2023 · carton.run · its alternatives →
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A native command-line interface for working with Apple Core ML models on macOS - schappim/coreml-cli
Jan 2026 · github.com · its alternatives →
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Deploy a ML inference service on a budget in less than 10 lines of code. - ebhy/budgetml
2021 · github.com · its alternatives →
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Apple MLX▲138An array framework for machine learning on Apple silicon
2023 · pypi.org · its alternatives →
- 10AW
student, nomad in machine learning
2019 · littlemountainman.github.io · its alternatives →
- 11
built a tiny pytorch clone in c after going through prof. vijay janapa reddi's mlsys book: mlsysbook.ai/tinytorch/ perfect for learning how ml frameworks work under the hood :)
Dec 2025 · github.com · its alternatives →
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Neural network inference the Unix way. Contribute to cloudkj/layer development by creating an account on GitHub.
2019 · github.com · its alternatives →
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Contribute to xadrianzetx/fullstack.ai development by creating an account on GitHub.
2019 · github.com · its alternatives →
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ML Console is a free tool to build an AI model without writing a single line of code. Simply pick a column to predict, and let us handle the rest.
2021 · mlconsole.com · its alternatives →
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A Linux desktop in the cloud built for Machine Learning
2016 · its alternatives →
- 17
I'm a machine learning engineer who always found it annoying to integrate ML models into phone apps, smartwatch apps, microcontroller firmware etc... Why do we need all these libraries and runtimes with all the overhead, compatibility issues and other headaches, when it's just some math to be executed? So I made a compiler that simply converts the model into plain source code with no dependencies, and it actually solved all my deployment problems. Now I'm curious if it can help anyone else too. Through the link you can submit your model file (Keras h5, onnx soon to be supported), and I'll…
2023 · waveworks.dk · its alternatives →
- 18
Machine learning for mobile developers
2018 · developers.google.com · its alternatives →
- 19PA
2014 · blog.michaelsu.io · its alternatives →
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This is a bunch of code to port Keras neural network model into pure C++. - pplonski/keras2cpp
2017 · github.com · its alternatives →
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We wrote our inference engine on Rust, it is faster than llama cpp in all of the use cases. Your feedback is very welcomed. Written from scratch with idea that you can add support of any kernel and platform.
2025 · github.com · its alternatives →
- 22DS
2020 · inferrd.com · its alternatives →
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Hi HN, I’ve been working on an OCR pipeline specifically optimized for machine learning dataset preparation. It’s designed to process complex academic materials — including math formulas, tables, figures, and multilingual text — and output clean, structured formats like JSON and Markdown. Some features: • Multi-stage OCR combining DocLayout-YOLO, Google Vision, MathPix, and Gemini Pro Vision • Extracts and understands diagrams, tables, LaTeX-style math, and multilingual text (Japanese/Korean/English) • Highly tuned for ML training pipelines, including dataset generation and…
2025 · github.com · its alternatives →
- 24
ChunkHound’s goal is simple: local-first codebase intelligence that helps you pull deep, core-dev-level insights on demand, generate always-up-to-date docs, and scale from small repos to enterprise monorepos — while staying free + open source and provider-agnostic (VoyageAI / OpenAI / Qwen3, Anthropic / OpenAI / Gemini / Grok, and more). I’d love your feedback — and if you have, thank you for being part of the journey!
Jan 2026 · github.com · its alternatives →
Also compare
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- MindsDB alternatives
- Igel – A CLI tool to run machine learning without writing code alternatives
- High-performance ahead-of-time compiler for Machine Learning alternatives
- Carton – Run any ML model from any programming language alternatives
- CLI for working with Apple Core ML models alternatives
Ranked by how close each launch is in meaning, then by votes. Prices were read from each product’s own site when checked and can change. Refine with your own description →