Life & fun · alternatives · 2026

24 alternatives to Curated, Pre-trained ML Models for Transfer Learning

Model Depot provides a collection of pre-trained machine learning models designed for transfer learning, with a focus on large language models. The platform helps users compare large language models by visualizing the… Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes. Curated, Pre-trained ML Models for Transfer Learning launched in 2018; newer entries below may have overtaken it.

1TA
Turn a low res image to high res with ML▲13
2018 · modeldepot.io · its alternatives →
2SE
Search engine for 20,000+ machine learning models▲18
2018 · modeldepot.io · its alternatives →
3DA
Deploy and Retrain Cutting Edge ML Image Recognition via REST API▲13
2018 · modeldepot.io · its alternatives →
4
ModelDepot▲108
Curated Machine Learning models to ⚡supercharge⚡your product
2018 · modeldepot.io · its alternatives →
5
Lobe▲1,236
Visual tool for building custom deep learning models
2018 · github.com · its alternatives →
6
Recraft Image Model▲304
First AI with high-quality images in user-uploaded style
2024 · its alternatives →
7
Plexe▲273
Build and deploy ML models in English
Oct 2025 · plexe.ai · its alternatives →
8
Fullstack ML – From Notebooks to Deployment▲198
Contribute to xadrianzetx/fullstack.ai development by creating an account on GitHub.
2019 · github.com · its alternatives →
9
Pretrained AI▲144
Integrate pretrained machine learning models in minutes.
2021 · pretrained.ai · its alternatives →
10
Roboflow Universe▲237
Pre-trained computer vision models and public datasets
2021 · universe.roboflow.com · its alternatives →
11
Zoo▲234
A free, open-source playground for AI image models
2023 · zoo.replicate.dev · its alternatives →
12
MLConsole – web app to train ML models, for free and client-side▲86
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 →
13
Machine Learning Playground▲169
Breathtaking visuals for learning ML techniques.
2017 · ml-playground.com · its alternatives →
14DA
depot.ai – easily embed ML / AI models in your Dockerfile▲7
Hey HN! We're excited to launch https://depot.ai today - depot.ai is an open-source Docker registry that makes it easy to embed public models from Hugging Face in your Docker images using a `COPY`: # Copy all files from the model repo to the current WORKDIR COPY --link --from=depot.ai/runwayml/stable-diffusion-v1-5 / . # COPY just one file from the model repo to the current WORKDIR COPY --link --from=depot.ai/runwayml/stable-diffusion-v1-5 /v1-5-pruned.ckpt . To optimize build speed, cache hits, and registry storage, we're building each image…
2023 · its alternatives →
15
Set of trained deep learning models for computer vision▲127
Keras code and weights files for popular deep learning models. - fchollet/deep-learning-models
2016 · github.com · its alternatives →
16
PerceptiLabs▲82
A tool to build your machine learning model at warp speed
2020 · perceptilabs.com · its alternatives →
17
Deploy ML Models on a Budget▲117
Deploy a ML inference service on a budget in less than 10 lines of code. - ebhy/budgetml
2021 · github.com · its alternatives →
18
Plexe – ML Models from a Prompt▲130
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 →
19
Transfer, easy transfer learning for image classification▲34
Contribute to matthew-sochor/transfer development by creating an account on GitHub.
2018 · github.com · its alternatives →
20
Compile ML models into dependency-free source code for easy deployment▲37
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 →
21MZ
Model Zoo: Deploy your machine learning model in a single line of code▲34
Informasi Akurat, Berita Terupdate – Hanya di Sini
2020 · modelzoo.dev · its alternatives →
22CI
Convect – Instant Serverless Deployment of ML Models▲89
2021 · convect.ml · its alternatives →
23
ModelDepot Percept▲6
🤖Deploy and Retrain ML Image Recognition 👀 in minutes
2018 · modeldepot.io · its alternatives →
24
Model2vec – Lightning-fast Static Embeddings for RAG/Semantic Search▲28
We’ve recently open-sourced Model2vec, a method to distill sentence transformers into static embeddings that outperform all previous approaches by a large margin on MTEB. Our new models set a new state-of-the-art for static embeddings. Main features: - Our best model (potion-base-8M) has only 8M parameters, which is ~30mb on disk - Inference is ~500x faster than the distilled base model (bge-base), on a CPU - New models can be distilled in 30 seconds on a CPU without requiring a dataset - just a vocabulary - Numpy-only inference: The packaged can be install the package with minimal…
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 →