RankLLMCastorini
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Related Products
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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.
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About
The fastest path to relevant recommendations and search. Increase engagement, conversion, and revenue with a configurable system that adapts in real time. We help your users find what they're looking for by surfacing the products or content that are most relevant to them. We do this whilst taking into account your business objectives to ensure all sides of your platform or marketplace are being optimized fairly. Under the hood, Shaped is a real-time, 4-stage, recommendation system containing all the data and machine-learning infrastructure needed to understand your data and serve your discovery use-case at scale. Connect and deploy rapidly with direct integration to your existing data sources. Ingest and re-rank in real-time using behavioral signals. Fine-tune LLMs and neural ranking models for state-of-the-art performance. Build and experiment with ranking and retrieval components for any use case.
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Audience
Academic researchers and developers seeking a solution offering tools for implementing and evaluating listwise reranking with large language models
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Audience
Businesses seeking a platform for recommendations, search and discovery
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Support
Phone Support
24/7 Live Support
Online
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Support
Phone Support
24/7 Live Support
Online
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API
Offers API
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API
Offers API
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Screenshots and Videos |
Screenshots and Videos |
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Pricing
Free
Free Version
Free Trial
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Pricing
No information available.
Free Version
Free Trial
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Reviews/
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Reviews/
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Training
Documentation
Webinars
Live Online
In Person
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Training
Documentation
Webinars
Live Online
In Person
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Company InformationCastorini
Canada
github.com/castorini/rank_llm/
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Company InformationShaped
United States
www.shaped.ai/
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Alternatives |
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Categories |
Categories |
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Integrations
AccessOwl
Amazon Kinesis
Amazon Redshift
Amazon S3
Gemini
Gemini Enterprise
Google Analytics
Google Cloud BigQuery
Google Cloud Firestore
Llama
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Integrations
AccessOwl
Amazon Kinesis
Amazon Redshift
Amazon S3
Gemini
Gemini Enterprise
Google Analytics
Google Cloud BigQuery
Google Cloud Firestore
Llama
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