Calculate GPU requirements for running LLMs
GIFT-Eval: A Benchmark for General Time Series Forecasting
Optimize and train foundation models using IBM's FMS
Evaluate reward models for math reasoning
Upload a machine learning model to Hugging Face Hub
Measure over-refusal in LLMs using OR-Bench
Evaluate code generation with diverse feedback types
Evaluate model predictions with TruLens
Persian Text Embedding Benchmark
View RL Benchmark Reports
Multilingual Text Embedding Model Pruner
View NSQL Scores for Models
Evaluate open LLMs in the languages of LATAM and Spain.
Can You Run It? LLM version is a specialized tool designed to calculate and verify the GPU requirements for running large language models (LLMs). It helps users determine if their system meets the necessary specifications to efficiently operate LLMs, ensuring optimal performance and compatibility.
• GPU Compatibility Check: Analyzes your system's GPU to ensure it meets the minimum requirements for running LLMs.
• System Resource Analysis: Evaluates CPU, RAM, and VRAM to provide a comprehensive hardware assessment.
• Performance Prediction: Estimates how smoothly an LLM will run on your system based on its specifications.
• Customizable Parameters: Allows users to input specific model parameters to tailor the analysis to their needs.
• User-Friendly Interface: Provides clear and actionable recommendations for upgrading or optimizing your system if needed.
What does Can You Run It? LLM version do?
Can You Run It? LLM version is a tool that checks if your system meets the hardware requirements to run large language models (LLMs) effectively. It provides detailed recommendations to ensure optimal performance.
Do I need to create an account to use the tool?
No, you do not need to create an account to use Can You Run It? LLM version. The tool is designed to be used directly on your system without requiring any sign-up or login.
What if my system doesn't meet the requirements?
If your system doesn't meet the requirements, the tool will provide specific recommendations, such as upgrading your GPU, increasing RAM, or optimizing your system settings to improve performance.