DeepScaleR - AI Model Development Tool

Overview

DeepScaleR is an open-source project that democratizes reinforcement learning (RL) for large language models (LLMs). It provides the artifacts researchers need to reproduce and scale RL techniques on LLMs. The repository includes training scripts, model checkpoints, detailed hyperparameter configurations, datasets, and evaluation logs to support reproducibility and research in advanced AI training.

Key Features

• Training scripts for reinforcement learning on large language models
• Provided model checkpoints for experiment reproducibility
• Detailed hyperparameter configurations and experiment metadata
• Bundled datasets and data-loading utilities
• Evaluation logs and scripts to reproduce published metrics
• Open-source GitHub repository with example workflows

Ideal Use Cases

• Reproduce RL experiments on LLMs
• Research and compare RL algorithms at scale
• Benchmark training recipes and hyperparameter choices
• Inspect model checkpoints and evaluation logs for auditing
• Develop or extend RL-based fine-tuning pipelines

Getting Started

• Clone the agentica-project/deepscaler GitHub repository
• Read the repository README and documentation
• Install dependencies listed in the repository
• Download provided model checkpoints and datasets
• Run an example training script to reproduce experiments
• Adjust hyperparameters and rerun training for your experiments

Pricing

Open-source repository; no pricing information disclosed.

Key Information

• Category: Model Development
• Type: AI Model Development Tool