Optimize and train foundation models using IBM's FMS
Browse and submit model evaluations in LLM benchmarks
Open Persian LLM Leaderboard
Benchmark AI models by comparison
Merge machine learning models using a YAML configuration file
Calculate survival probability based on passenger details
Calculate memory needed to train AI models
Export Hugging Face models to ONNX
Browse and filter machine learning models by category and modality
Measure BERT model performance using WASM and WebGPU
Multilingual Text Embedding Model Pruner
Predict customer churn based on input details
Evaluate RAG systems with visual analytics
README is an essential tool designed to optimize and train foundation models using IBM's Foundation Model Services (FMS). It falls under the category of model benchmarking and is tailored to help users streamline their model training processes. README serves as a comprehensive guide to leveraging IBM's advanced AI model optimization capabilities.
• Model Optimization: Fine-tune your foundation models for specific tasks and datasets.
• Integration with IBM FMS: Seamlessly connect with IBM's powerful AI infrastructure for scalable training.
• Cloud-Based: Operate entirely in the cloud, eliminating the need for local hardware.
• Advanced Benchmarking: Compare and analyze model performance metrics with precision.
• Extensibility: Adapt the tool to suit your unique workflow and project requirements.
What models does README support?
README is optimized for use with IBM's foundation models, including but not limited to their latest AI releases.
How are benchmarking results provided?
Results are delivered as detailed reports, providing metrics such as accuracy, latency, and computational efficiency.
Where can I find additional support?
For further assistance, visit the official IBM FMS documentation or contact their support team directly.