Toloka ML Platform now available in beta!

Toloka Team
by Toloka Team

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We're excited to announce that Toloka has released the beta version of our new ML Platform, designed to deliver custom ML models in just a few clicks.

No need for ML infrastructure — choose a pre-trained model that matches your task, adapt it to fit your data, and access it via API.

  • Auto-training fine-tunes the model for you. All you need is data.
  • Covers almost every data type — text, image, and video (expanded support coming soon).
  • Built-in data labeling. Do it yourself in our handy tool or send it to the Toloka crowd.
  • Easy deployment and model hosting with low-latency inference.
  • Experiment metadata stored on the platform.
  • Completely free for early adopters (up to 3 models).

ML model use cases

Here are some examples of tasks that our ML models can handle. Feel free to reach out to with your project needs. We can point you to the right model or provide a customized solution.

  • Analyze and moderate user reviews
  • Classify products by category
  • Generate product descriptions
  • Check product similarity for search and recommendation systems
Customer Service
  • Classify support requests
  • Analyze chatbot input
  • Generate responses to support requests
  • Answer questions in knowledge base or community
  • Summarize chats with customers
  • Detect toxic content, spam, watermarks
  • Moderate UGC
  • Brand monitoring
  • Generate image captions
  • Generate illustrations for any online content
  • Summarize articles
  • Summarize brand mentions
  • Moderate ad content (text & image)
  • Detect clickbait
  • Generate ad text or headlines
  • Generate images for ads
  • Object detection in images
  • Speech recognition

Try out the Toloka ML platform

Just jump right in to explore the platform capabilities and try out some of the pre-trained models.


To get started, you'll go through these basic steps:

  1. Sign up and log into the platform.
  2. Choose a pre-trained model from our catalog.
  3. For fine-tuning, upload your training data in CSV format. Use our visual data labeling tool to add labels or check existing labels in your dataset after uploading.
  4. Run auto training to tune the model using the data you uploaded.
  5. Find your model in the registry, run it, and check the quality of responses. You can apply the trained model to a dataset offline or deploy the model as a service on Toloka and access it via API for inference in your application.

For a visual guide, follow the steps and videos in How it works on the platform.

If you need help, click the Get expert help button and submit your questions — we'll help you choose the best model for your needs and adapt it to your task.

Get expert help

Beta is free, including storage and usage — now's the perfect time to test it out!

Not sure where to start? Wondering if there's a model that can handle your task? Just drop us a line at — we'll be happy to help.

Article written by:
Toloka Team
Toloka Team

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