RankLLM

RankLLM

Castorini
+
+

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About

RankLLM is a Python toolkit for reproducible information retrieval research using rerankers, with a focus on listwise reranking. It offers a suite of rerankers, pointwise models like MonoT5, pairwise models like DuoT5, and listwise models compatible with vLLM, SGLang, or TensorRT-LLM. Additionally, it supports RankGPT and RankGemini variants, which are proprietary listwise rerankers. It includes modules for retrieval, reranking, evaluation, and response analysis, facilitating end-to-end workflows. RankLLM integrates with Pyserini for retrieval and provides integrated evaluation for multi-stage pipelines. It also 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.

About

Symflower enhances software development by integrating static, dynamic, and symbolic analyses with Large Language Models (LLMs). This combination leverages the precision of deterministic analyses and the creativity of LLMs, resulting in higher quality and faster software development. Symflower assists in identifying the most suitable LLM for specific projects by evaluating various models against real-world scenarios, ensuring alignment with specific environments, workflows, and requirements. The platform addresses common LLM challenges by implementing automatic pre-and post-processing, which improves code quality and functionality. By providing the appropriate context through Retrieval-Augmented Generation (RAG), Symflower reduces hallucinations and enhances LLM performance. Continuous benchmarking ensures that use cases remain effective and compatible with the latest models. Additionally, Symflower accelerates fine-tuning and training data curation, offering detailed reports.

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

Academic researchers and developers seeking a solution offering tools for implementing and evaluating listwise reranking with large language models

Audience

Software developers wanting a solution to improve software quality and build their applications

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

No information available.
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

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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

Castorini
Canada
github.com/castorini/rank_llm/

Company Information

Symflower
Founded: 2018
Austria
symflower.com

Alternatives

RankGPT

RankGPT

Weiwei Sun

Alternatives

Selene 1

Selene 1

atla
ColBERT

ColBERT

Future Data Systems

Categories

Categories

Integrations

Mistral AI
OpenAI
Qwen
Codestral
Cohere
Command R+
GPT-4
GPT-4 Turbo
GPT-4o
JUnit
Llama
Llama 3
Mathstral
Meta AI
Mistral 7B
Mistral Small
Mixtral 8x22B
Perplexity
Python

Integrations

Mistral AI
OpenAI
Qwen
Codestral
Cohere
Command R+
GPT-4
GPT-4 Turbo
GPT-4o
JUnit
Llama
Llama 3
Mathstral
Meta AI
Mistral 7B
Mistral Small
Mixtral 8x22B
Perplexity
Python
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Claim RankLLM and update features and information
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