A marketplace where people record and submit video, then get paid an hourly rate, to build up the training data that AI video models are trained on.
#fine-tuning
12 tools curated in this category — including RecipeBook, Unsloth, Kronos
techFind on mySelectas all sites and tools related to fine-tuning. This selection of 12 resources is reviewed and maintained by the community. The most popular include RecipeBook, Unsloth, Kronos. Each tool comes with a review, tags, comparisons and alternatives to help you make the best choice.
Training your own AI model usually means renting expensive cloud GPUs for hours — Unsloth lets you fine-tune popular open models on your own computer, 2 to 30 times faster and using far less memory than the standard tools.
A free AI model trained specifically on stock and crypto price charts (rather than general text) that tries to predict where a market might move next, similar to how a language model predicts the next word.
A free tool that lets a regular desktop computer run huge AI models that would normally need a room full of expensive server GPUs, by splitting the work smartly between your CPU and your (much smaller) GPU.
A service that trains a small, specialized AI model tailored to one specific task instead of using a giant general-purpose model for everything, at a fraction of the usual cost.
Arkor lets your AI coding assistant write the training code for a custom AI model, then handles the expensive GPU work behind the scenes — so fine-tuning a model no longer requires being a machine-learning engineer.
A European, publicly-traded cloud built specifically for AI workloads — GPU clusters, training, inference — for companies that want serious AI compute without depending on a US hyperscaler.
Data annotation and evaluation platform that turns raw images, video, text and audio into labeled datasets for training and fine-tuning AI models.
Pay-by-the-second GPU cloud for training and running AI models, with no contracts and fast serverless cold starts.
GPU cloud built for AI research and production, scaling from a single rented GPU up to superclusters with over 165,000 GPUs.
Data platform for labeling, curating and generating human feedback to train and fine-tune AI models, including reinforcement learning workflows.
Cloud inference platform for running and fine-tuning open-source language models fast, without owning any GPUs.