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What is vLLM?

vLLM is an innovative library specifically designed for the efficient inference and deployment of Large Language Models (LLMs). Originally developed at UC Berkeley's Sky Computing Lab, it has evolved into a collaborative project that benefits from input by both academia and industry. The library stands out for its remarkable serving throughput, achieved through its unique PagedAttention mechanism, which adeptly manages attention key and value memory. It supports continuous batching of incoming requests and utilizes optimized CUDA kernels, leveraging technologies such as FlashAttention and FlashInfer to enhance model execution speed significantly. In addition, vLLM accommodates several quantization techniques, including GPTQ, AWQ, INT4, INT8, and FP8, while also featuring speculative decoding capabilities. Users can effortlessly integrate vLLM with popular models from Hugging Face and take advantage of a diverse array of decoding algorithms, including parallel sampling and beam search. It is also engineered to work seamlessly across various hardware platforms, including NVIDIA GPUs, AMD CPUs and GPUs, and Intel CPUs, which assures developers of its flexibility and accessibility. This extensive hardware compatibility solidifies vLLM as a robust option for anyone aiming to implement LLMs efficiently in a variety of settings, further enhancing its appeal and usability in the field of machine learning.

What is Hugging Face?

Hugging Face is an AI-driven platform designed for developers, researchers, and businesses to collaborate on machine learning projects. The platform hosts an extensive collection of pre-trained models, datasets, and tools that can be used to solve complex problems in natural language processing, computer vision, and more. With open-source projects like Transformers and Diffusers, Hugging Face provides resources that help accelerate AI development and make machine learning accessible to a broader audience. The platform’s community-driven approach fosters innovation and continuous improvement in AI applications.

Media

Media

Integrations Supported

Database Mart
AWS EC2 Trn3 Instances
Aurascape
Axolotl
Chainlit
CrewAI
DagsHub
Devstral
Ekinox
FauxPilot
Gemma 3
Intel Open Edge Platform
Langfuse
Naptha
ONTEC AI
Portia
StackAI
Supastarter
Tiger Data
garak

Integrations Supported

Database Mart
AWS EC2 Trn3 Instances
Aurascape
Axolotl
Chainlit
CrewAI
DagsHub
Devstral
Ekinox
FauxPilot
Gemma 3
Intel Open Edge Platform
Langfuse
Naptha
ONTEC AI
Portia
StackAI
Supastarter
Tiger Data
garak

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

$9 per month
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

vLLM

Company Location

United States

Company Website

vllm.ai

Company Facts

Organization Name

Hugging Face

Date Founded

2016

Company Location

United States

Company Website

huggingface.co

Categories and Features

Categories and Features

Artificial Intelligence

Chatbot
For Healthcare
For Sales
For eCommerce
Image Recognition
Machine Learning
Multi-Language
Natural Language Processing
Predictive Analytics
Process/Workflow Automation
Rules-Based Automation
Virtual Personal Assistant (VPA)

Machine Learning

Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization

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