AI · alternatives · 2026
24 alternatives to Carton – Run any ML model from any programming language
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…
Carton is a tool that provides a unified interface for running machine learning models from any programming language, regardless of the framework used to build them. It isolates models in separate processes to avoid… Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes. Carton – Run any ML model from any programming language launched in 2023; newer entries below may have overtaken it.
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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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TensorFlow 1.0▲823Open-source machine learning library by Google
2017 · tensorflow.org · its alternatives →
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My Machine Learning Web Service. Contribute to pplonski/my_ml_service development by creating an account on GitHub.
2020 · 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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We've been hard at work for a few weeks and thought it's time for another update. In case you missed our first post, PostgresML is an end-to-end machine learning solution, running alongside your favorite database. This time we have more of a suite offering: project management, visibility into the datasets and the deployment pipeline decision making. Let us know what you think! Demo link is on the page, and also here: https://demo.postgresml.org
2022 · postgresml.org · its alternatives →
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Hi HN! We’re excited to share marimo, an open-source reactive notebook for Python [1]. marimo aims to solve well-known problems with traditional notebooks [2]: marimo notebooks are reproducible (no hidden state), git-friendly (stored as Python files), executable as Python scripts, and deployable as web apps. GitHub repo: https://github.com/marimo-team/marimo In marimo, a notebook’s code, outputs, and program state are always consistent. Run a cell and marimo reacts by automatically running the cells that reference its declared variables. Delete a cell and marimo scrubs…
2024 · github.com · its alternatives →
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TensorZero▲307Hi HN! We're Gabriel & Viraj, and we're excited to open source TensorZero. To be a little cheeky, TensorZero is an open-source platform that helps LLM applications graduate from API wrappers into defensible AI products. 1. Integrate our model gateway 2. Send metrics or feedback 3. Unlock compounding improvements in quality, cost, and latency It enables a data & learning flywheel for LLMs by unifying: • Inference: one API for all LLMs, with <1ms P99 overhead • Observability: inference & feedback → your database • Optimization: better prompts, models, inference strategies • Experimentation:…
2025 · github.com · its alternatives →
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I've been playing around with https://github.com/zphang/minimal-llama/ and https://github.com/tloen/alpaca-lora/blob/main/finetune.py, and wanted to create a simple UI where you can just paste text, tweak the parameters, and finetune the model quickly using a modern GPU. To prepare the data, simply separate your text with two blank lines. There's an inference tab, so you can test how the tuned model behaves. This is my first foray into the world of LLM finetuning, Python, Torch, Transformers, LoRA, PEFT, and Gradio. Enjoy!
2023 · github.com · its alternatives →
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Hey there HN! We're Esteban and Esteban and we are looking to get feedback for the new version of our GPT-powered, open-source code contextualizer. We're starting with a VS Code extension that indexes information from git (GitHub, GitLab, or Bitbucket integrations available), Slack and Jira to explain the context around a file or block of code. Finally, we summarize such aggregated context using the power of GPT. As devs we know that it's very annoying to look at a new codebase and start understanding all the nuances, particularly when the person who wrote the code already left the company.…
2023 · watermelontools.com · its alternatives →
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Machine learning for mobile developers
2018 · developers.google.com · its alternatives →
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Hey HN! We’re Vaibhav and Marcello. We’re building Plexe (https://github.com/plexe-ai/plexe), an open-source agent that turns natural language task descriptions into trained ML models. Here’s a video walkthrough: https://www.youtube.com/watch?v=bUwCSglhcXY. There are all kinds of uses for ML models that never get realized because the process of making them is messy and convoluted. You can spend months trying to find the data, clean it, experiment with models and deploy to production, only to find out that your project has been binned for taking so long.…
2025 · github.com · its alternatives →
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Build and share delightful machine learning apps, all in Python. 🌟 Star to support our work! - gradio-app/gradio
2020 · github.com · its alternatives →
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Hi HN! Last year, we shared marimo [1], an open-source reactive notebook for Python with support for execution through WebAssembly [2]. We wanted to share something new: you can now run marimo and Jupyter notebooks directly from GitHub in a Wasm-powered, codespace-like environment. What makes this powerful is that we mount the GitHub repository's contents as a filesystem in the notebook, making it really easy to share notebooks with data. All you need to do is prepend 'marimo.app' to any Python notebook on GitHub. Some examples: - Jupyter Notebook:…
2025 · docs.marimo.io · its alternatives →
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Hi HN, Three months ago, I took a job at Baseten to help craft and document an application builder that lets data scientists build full-stack, production-ready applications around their ML models without worrying about containers, Flask, or React. From my first day, everyone was focused on what would happen today: opening up our public beta. I’m super excited to see what you build with Baseten. If you want to take Baseten for a full-speed test drive, follow along with this tutorial, where you can build and deploy an application in 20 minutes:…
2022 · baseten.co · its alternatives →
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I started building a couple of years ago because I found no easy existing solution to build Slack bots that can be composed from/organized into plugins. Existing libraries like Bolt make it pretty easy to develop Slack bots, but hard to organize and scale the code base of your bot. I was also missing some crucial features such as scheduling actions for your bot. So I wrote my own framework! I recently rewrote the complete framework to make use of asyncio and the newest Slack SDK Let me know what you think!
2022 · github.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 →
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GoLearn▲81Machine Learning for Go. Contribute to sjwhitworth/golearn development by creating an account on GitHub.
2014 · github.com · its alternatives →
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Google colab GPU access in every language - not just Python
2024 · github.com · its alternatives →
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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 →