Optimize and train foundation models using IBM's FMS
SolidityBench Leaderboard
Evaluate adversarial robustness using generative models
Merge Lora adapters with a base model
Explore and manage STM32 ML models with the STM32AI Model Zoo dashboard
View and submit LLM benchmark evaluations
Browse and filter machine learning models by category and modality
Predict customer churn based on input details
Quantize a model for faster inference
Browse and submit model evaluations in LLM benchmarks
Convert and upload model files for Stable Diffusion
Benchmark LLMs in accuracy and translation across languages
Download a TriplaneGaussian model checkpoint
README is a tool designed to help users optimize and train foundation models using IBM's Foundation Model Services (FMS). It provides a streamlined approach to benchmarking, optimizing, and deploying models efficiently.
• Model Benchmarking: Compare performance across different foundation models. • Optimization: Use IBM's FMS to fine-tune models for specific tasks. • Scalability: Handles large-scale datasets and complex training workloads. • Integration: Seamless integration with IBM's ecosystem of AI tools. • Analytics: Gain insights into model performance with detailed metrics.
What is IBM's Foundation Model Services (FMS)?
IBM's FMS is a suite of tools designed to help developers train, deploy, and manage foundation models at scale.
Can I use README with any foundation model?
README is optimized for use with models supported by IBM's FMS. Check compatibility before use.
Do I need special hardware to run README?
README is designed to run on standard computing environments but may benefit from GPU acceleration for faster training and benchmarking.