Optimize and train foundation models using IBM's FMS
Load AI models and prepare your space
Explore GenAI model efficiency on ML.ENERGY leaderboard
Create demo spaces for models on Hugging Face
Analyze model errors with interactive pages
Calculate memory needed to train AI models
Calculate VRAM requirements for LLM models
Explain GPU usage for model training
Download a TriplaneGaussian model checkpoint
GIFT-Eval: A Benchmark for General Time Series Forecasting
Generate and view leaderboard for LLM evaluations
Evaluate AI-generated results for accuracy
Benchmark AI models by comparison
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.