Optimize and train foundation models using IBM's FMS
Measure BERT model performance using WASM and WebGPU
Create and upload a Hugging Face model card
Browse and submit language model benchmarks
Explore and benchmark visual document retrieval models
Measure execution times of BERT models using WebGPU and WASM
Explore and manage STM32 ML models with the STM32AI Model Zoo dashboard
SolidityBench Leaderboard
Evaluate open LLMs in the languages of LATAM and Spain.
Browse and filter machine learning models by category and modality
Run benchmarks on prediction models
Explore and visualize diverse models
Text-To-Speech (TTS) Evaluation using objective metrics.
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.