Optimize and train foundation models using IBM's FMS
Predict customer churn based on input details
Evaluate reward models for math reasoning
Display and filter leaderboard models
Track, rank and evaluate open LLMs and chatbots
View and submit machine learning model evaluations
Explore and benchmark visual document retrieval models
Compare code model performance on benchmarks
Merge Lora adapters with a base model
Measure over-refusal in LLMs using OR-Bench
Download a TriplaneGaussian model checkpoint
Calculate memory needed to train AI models
Display genomic embedding 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.