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This project is a GUI for the gpustack/gguf-parser-go
Analyze and visualize your dataset using AI
The LLM Model VRAM Calculator is a tool designed to help users estimate the VRAM (Video Random Access Memory) requirements for running large language models (LLMs). It provides a user-friendly way to calculate the memory needed to ensure optimal performance when deploying or using these models, helping to prevent issues like memory overflow or inefficient resource utilization.
• Accuracy: Provides precise VRAM estimates based on model size and architecture.
• Model Support: Compatible with a wide range of large language models, including popular architectures like GPT, BERT, and others.
• GPU Compatibility: Offers calculations tailored to specific GPU models, ensuring accurate results for different hardware configurations.
• User-Friendly Interface: Intuitive design makes it easy to input parameters and interpret results.
• Batch Processing: Ability to calculate VRAM requirements for multiple models simultaneously.
• Export Options: Results can be exported for further analysis or reporting.
What model parameters are required for accurate calculations?
You will need to provide the model's architecture, number of layers, hidden size, and attention head count for the most accurate results.
Can the calculator support custom or less common models?
Yes, the calculator allows users to input custom model parameters, making it adaptable to a wide range of architectures beyond the pre-loaded options.
How does the calculator account for different GPU architectures?
The calculator uses GPU-specific memory allocation algorithms to ensure accurate estimates, taking into account the unique characteristics of each supported GPU model.