Optimize and train foundation models using IBM's FMS
View and compare language model evaluations
Upload a machine learning model to Hugging Face Hub
Convert Stable Diffusion checkpoint to Diffusers and open a PR
Find recent high-liked Hugging Face models
Explore and submit models using the LLM Leaderboard
Evaluate adversarial robustness using generative models
Browse and filter machine learning models by category and modality
Create and upload a Hugging Face model card
Track, rank and evaluate open LLMs and chatbots
Browse and submit LLM evaluations
Measure execution times of BERT models using WebGPU and WASM
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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.