Calculate memory usage for LLM models
Create and upload a Hugging Face model card
Evaluate LLM over-refusal rates with OR-Bench
Rank machines based on LLaMA 7B v2 benchmark results
Push a ML model to Hugging Face Hub
View and submit LLM benchmark evaluations
Merge Lora adapters with a base model
Compare and rank LLMs using benchmark scores
Display and submit LLM benchmarks
Determine GPU requirements for large language models
Calculate survival probability based on passenger details
Track, rank and evaluate open LLMs and chatbots
Upload a machine learning model to Hugging Face Hub
Llm Memory Requirement is a tool designed to calculate and benchmark memory usage for Large Language Models (LLMs). It helps users understand the memory demands of different LLMs, enabling informed decisions for model deployment and optimization.
• Memory Calculation: Accurately computes memory usage for various LLM configurations.
• Model Optimization: Provides recommendations to reduce memory consumption.
• Benchmarking: Comparisons across different LLMs for performance evaluation.
• Cross-Compatibility: Supports multiple frameworks and hardware setups.
• User-Friendly Interface: Simplifies complex memory analysis for ease of use.
What is the purpose of Llm Memory Requirement?
Llm Memory Requirement helps users understand and optimize memory usage for Large Language Models, ensuring efficient deployment.
How do I input model parameters?
Parameters like model size, architecture, and precision can be inputted through the tool's interface or via command-line arguments.
Can the tool work with any LLM?
Yes, it supports most modern LLMs and frameworks, including popular ones like Transformers and Megatron.