Cloud inference platform for running and fine-tuning open-source language models fast, without owning any GPUs.
Results for “fine-tuning”
17 tools found
Data platform for labeling, curating and generating human feedback to train and fine-tune AI models, including reinforcement learning workflows.
GPU cloud built for AI research and production, scaling from a single rented GPU up to superclusters with over 165,000 GPUs.
Pay-by-the-second GPU cloud for training and running AI models, with no contracts and fast serverless cold starts.
Data annotation and evaluation platform that turns raw images, video, text and audio into labeled datasets for training and fine-tuning AI models.
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.
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 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.
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 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.
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 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.
Open-source CLI that automatically removes safety-alignment refusals from open-weight language models using directional ablation, without retraining.
Marketplace where developers can discover, A/B test, and deploy fine-tuned LLM adapters with one click, and where model creators can host and monetize their own fine-tunes with a 70/30 revenue split.
An open-source experiment where an AI agent designs and trains its own smaller language models using reinforcement learning, for about $1,300 in GPU costs.
Model inference and fine-tuning
Open-source Python CLI that turns technical documentation into clean Q&A training datasets for LLM fine-tuning, using a local model.