AirLLM Inference

Overview

AirLLM Inference is a state-of-the-art project designed for efficient inference of Large Language Models (LLMs) in various applications. This repository contains implementations and guidelines to help developers utilize advanced AI capabilities effectively.

Features

• Model Agnostic: Supports various LLMs including but not limited to GPT, BERT, and others.
• Easy to Use: Simple API for model interrogation, analysis, and deployment.
• High Performance: Optimized for speed and efficiency using state-of-the-art techniques.
• Scalable: Can be deployed in cloud environments and optimized for multi-GPU setups.

Installation

To get started with AirLLM Inference, simply clone the repository and install the requirements:

# Clone the repository
git clone https://github.com/kishor-m7/AirLLM-Inference.git
cd AirLLM-Inference

# Install required packages
pip install -r requirements.txt

Usage

Here's an example of how to use the AirLLM Inference library:

from airllm import AirLLMModel

# Load the model
model = AirLLMModel(model_name='gpt-3')

# Run inference
output = model.infer(prompt='What is the capital of France?')
print(output)