Optimize and train foundation models using IBM's FMS
Display leaderboard of language model evaluations
Search for model performance across languages and benchmarks
Rank machines based on LLaMA 7B v2 benchmark results
Quantize a model for faster inference
Create and upload a Hugging Face model card
Convert PaddleOCR models to ONNX format
Measure over-refusal in LLMs using OR-Bench
Browse and filter machine learning models by category and modality
Evaluate LLM over-refusal rates with OR-Bench
Explore and visualize diverse models
Find and download models from Hugging Face
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.