Calculate memory usage for LLM models
Convert a Stable Diffusion XL checkpoint to Diffusers and open a PR
Convert PyTorch models to waifu2x-ios format
Teach, test, evaluate language models with MTEB Arena
Push a ML model to Hugging Face Hub
Text-To-Speech (TTS) Evaluation using objective metrics.
Search for model performance across languages and benchmarks
Generate and view leaderboard for LLM evaluations
View and submit language model evaluations
Export Hugging Face models to ONNX
Evaluate open LLMs in the languages of LATAM and Spain.
Explore and manage STM32 ML models with the STM32AI Model Zoo dashboard
Evaluate adversarial robustness using generative models
Llm Memory Requirement is a tool designed to calculate and benchmark the memory usage of large language models (LLMs). It helps users understand the memory requirements for running LLMs, ensuring optimal performance and efficient resource allocation. This tool is particularly useful for developers, researchers, and organizations deploying LLMs in various applications.
What is the purpose of Llm Memory Requirement?
Llm Memory Requirement helps users understand and optimize the memory usage of large language models, ensuring efficient resource utilization and performance.
How do I interpret the memory usage reports?
The reports provide detailed insights into memory consumption, including peak usage and allocation patterns. Use these insights to identify bottlenecks and apply optimizations.
Can Llm Memory Requirement work with any LLM framework?
Yes, the tool is designed to support multiple LLM architectures and frameworks, making it versatile for different use cases.