Optimize and train foundation models using IBM's FMS
Calculate VRAM requirements for LLM models
Convert Hugging Face models to OpenVINO format
Compare LLM performance across benchmarks
Display leaderboard for earthquake intent classification models
View LLM Performance Leaderboard
Benchmark AI models by comparison
View and submit machine learning model evaluations
Rank machines based on LLaMA 7B v2 benchmark results
Push a ML model to Hugging Face Hub
Measure execution times of BERT models using WebGPU and WASM
Find recent high-liked Hugging Face models
Explain GPU usage for model training
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.