Optimize and train foundation models using IBM's FMS
Run benchmarks on prediction models
Rank machines based on LLaMA 7B v2 benchmark results
Evaluate and submit AI model results for Frugal AI Challenge
Measure execution times of BERT models using WebGPU and WASM
Explore and benchmark visual document retrieval models
Benchmark LLMs in accuracy and translation across languages
Export Hugging Face models to ONNX
Evaluate LLM over-refusal rates with OR-Bench
Compare LLM performance across benchmarks
Create and upload a Hugging Face model card
Upload a machine learning model to Hugging Face Hub
View and compare language model evaluations
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.