Related Products
|
||||||
About
VLLM is a high-performance library designed to facilitate efficient inference and serving of Large Language Models (LLMs). Originally developed in the Sky Computing Lab at UC Berkeley, vLLM has evolved into a community-driven project with contributions from both academia and industry. It offers state-of-the-art serving throughput by efficiently managing attention key and value memory through its PagedAttention mechanism. It supports continuous batching of incoming requests and utilizes optimized CUDA kernels, including integration with FlashAttention and FlashInfer, to enhance model execution speed. Additionally, vLLM provides quantization support for GPTQ, AWQ, INT4, INT8, and FP8, as well as speculative decoding capabilities. Users benefit from seamless integration with popular Hugging Face models, support for various decoding algorithms such as parallel sampling and beam search, and compatibility with NVIDIA GPUs, AMD CPUs and GPUs, Intel CPUs, and more.
|
About
Users enjoy personalized interactions, creating custom AI models to meet individual needs with decentralized technology, Navigator offers rapid, location-independent responses. Experience innovation where technology complements human expertise. Collaboratively create, manage, and monitor content with co-workers, friends, and AI. Build custom AI models in minutes vs hours. Revitalize large models with attention steering, streamlining training and cutting compute costs. Seamlessly translates user interactions into manageable tasks. It selects and executes the most suitable AI model for each task, delivering responses that align with user expectations. Private forever, with no back doors, distributed storage, and seamless inference. It leverages distributed, edge-friendly technology for lightning-fast interactions, no matter where you are. Join our vibrant distributed storage ecosystem, where you can unlock access to the world's first watermarked universal model dataset.
|
|||||
Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
|
Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
|
|||||
Audience
AI infrastructure engineers looking for a solution to optimize the deployment and serving of large-scale language models in production environments
|
Audience
Teams and individuals interested in a tool to create, manage, and monitor content
|
|||||
Support
Phone Support
24/7 Live Support
Online
|
Support
Phone Support
24/7 Live Support
Online
|
|||||
API
Offers API
|
API
Offers API
|
|||||
Screenshots and Videos |
Screenshots and Videos |
|||||
Pricing
No information available.
Free Version
Free Trial
|
Pricing
Free
Free Version
Free Trial
|
|||||
Reviews/
|
Reviews/
|
|||||
Training
Documentation
Webinars
Live Online
In Person
|
Training
Documentation
Webinars
Live Online
In Person
|
|||||
Company InformationVLLM
United States
docs.vllm.ai/en/latest/
|
Company InformationwebAI
www.webai.com
|
|||||
Alternatives |
Alternatives |
|||||
|
||||||
|
||||||
Categories |
Categories |
|||||
Integrations
Database Mart
Docker
Hugging Face
KServe
Kubernetes
Llama 3.1
NGINX
NVIDIA DRIVE
OpenAI
PyTorch
|
Integrations
Database Mart
Docker
Hugging Face
KServe
Kubernetes
Llama 3.1
NGINX
NVIDIA DRIVE
OpenAI
PyTorch
|
|||||
|
|