LiteRT

LiteRT

Google
RankGPT

RankGPT

Weiwei Sun
+
+

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About

LiteRT (Lite Runtime), formerly known as TensorFlow Lite, is Google's high-performance runtime for on-device AI. It enables developers to deploy machine learning models across various platforms and microcontrollers. LiteRT supports models from TensorFlow, PyTorch, and JAX, converting them into the efficient FlatBuffers format (.tflite) for optimized on-device inference. Key features include low latency, enhanced privacy by processing data locally, reduced model and binary sizes, and efficient power consumption. The runtime offers SDKs in multiple languages such as Java/Kotlin, Swift, Objective-C, C++, and Python, facilitating integration into diverse applications. Hardware acceleration is achieved through delegates like GPU and iOS Core ML, improving performance on supported devices. LiteRT Next, currently in alpha, introduces a new set of APIs that streamline on-device hardware acceleration.

About

RankGPT is a Python toolkit designed to explore the use of generative Large Language Models (LLMs) like ChatGPT and GPT-4 for relevance ranking in Information Retrieval (IR). It introduces methods such as instructional permutation generation and a sliding window strategy to enable LLMs to effectively rerank documents. It supports various LLMs, including GPT-3.5, GPT-4, Claude, Cohere, and Llama2 via LiteLLM. RankGPT provides modules for retrieval, reranking, evaluation, and response analysis, facilitating end-to-end workflows. It includes a module for detailed analysis of input prompts and LLM responses, addressing reliability concerns with LLM APIs and non-deterministic behavior in Mixture-of-Experts (MoE) models. The toolkit supports various backends, including SGLang and TensorRT-LLM, and is compatible with a wide range of LLMs. RankGPT's Model Zoo includes models like LiT5 and MonoT5, hosted on Hugging Face.

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

Mobile application developers in search of a tool to integrate efficient, on-device AI capabilities into their apps

Audience

AI researchers needing a tool to leverage LLMs for advanced document reranking in information retrieval systems

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

Free
Free Version
Free Trial

Pricing

Free
Free Version
Free Trial

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

Google
Founded: 1998
United States
ai.google.dev/edge/litert

Company Information

Weiwei Sun
United States
github.com/sunnweiwei/RankGPT

Alternatives

AWS Neuron

AWS Neuron

Amazon Web Services

Alternatives

RankLLM

RankLLM

Castorini
ColBERT

ColBERT

Future Data Systems

Categories

Categories

Integrations

Python
C++
ChatGPT
Claude
Cohere
GPT-3.5
GPT-4
Google AI Edge Gallery
Hugging Face
JAX
Java
Kotlin
LiteLLM
Llama 2
NVIDIA TensorRT
Objective-C
PyTorch
RankLLM
Swift
TensorFlow

Integrations

Python
C++
ChatGPT
Claude
Cohere
GPT-3.5
GPT-4
Google AI Edge Gallery
Hugging Face
JAX
Java
Kotlin
LiteLLM
Llama 2
NVIDIA TensorRT
Objective-C
PyTorch
RankLLM
Swift
TensorFlow
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