Optimize and train foundation models using IBM's FMS
Submit deepfake detection models for evaluation
Calculate survival probability based on passenger details
Benchmark LLMs in accuracy and translation across languages
Convert a Stable Diffusion XL checkpoint to Diffusers and open a PR
Submit models for evaluation and view leaderboard
Evaluate RAG systems with visual analytics
Explore and visualize diverse models
Browse and filter ML model leaderboard data
Text-To-Speech (TTS) Evaluation using objective metrics.
View and submit LLM benchmark evaluations
Benchmark models using PyTorch and OpenVINO
View LLM Performance Leaderboard
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.