RankLLMCastorini
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TensorBoardTensorflow
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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
TensorBoard is TensorFlow's comprehensive visualization toolkit designed to facilitate machine learning experimentation. It enables users to track and visualize metrics such as loss and accuracy, visualize the model graph (operations and layers), view histograms of weights, biases, or other tensors as they change over time, project embeddings to a lower-dimensional space, and display images, text, and audio data. Additionally, TensorBoard offers profiling capabilities to optimize TensorFlow programs. These features collectively provide a suite of tools to understand, debug, and optimize TensorFlow programs, enhancing the machine learning workflow. In machine learning, to improve something you often need to be able to measure it. TensorBoard is a tool for providing the measurements and visualizations needed during the machine learning workflow. It enables tracking experiment metrics, visualizing the model graph, and projecting embeddings to a lower dimensional space.
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Platforms Supported
Windows
Not Supported
Mac
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Linux
Not Supported
Cloud
Supported
On-Premises
Not Supported
iPhone
Not Supported
iPad
Not Supported
Android
Not Supported
Chromebook
Not Supported
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Platforms Supported
Windows
Not Supported
Mac
Not Supported
Linux
Not Supported
Cloud
Supported
On-Premises
Not Supported
iPhone
Not Supported
iPad
Not Supported
Android
Not Supported
Chromebook
Not Supported
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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
Developers looking for a solution to optimize their TensorFlow programs
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Support
Phone Support
Not Supported
24/7 Live Support
Not Supported
Online
Supported
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Support
Phone Support
Supported
24/7 Live Support
Not Supported
Online
Supported
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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
Supported
Free Trial
Not Supported
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Pricing
Free
Free Version
Supported
Free Trial
Not Supported
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Reviews/
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Reviews/
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Training
Documentation
Supported
Webinars
Not Supported
Live Online
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In Person
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Training
Documentation
Supported
Webinars
Not Supported
Live Online
Not Supported
In Person
Supported
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Company InformationCastorini
Canada
github.com/castorini/rank_llm/
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Company InformationTensorflow
United States
www.tensorflow.org/tensorboard
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Categories |
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Integrations
Dataoorts GPU Cloud
Not Supported
Gemini
Supported
Gemini Enterprise
Supported
GitHub
Not Supported
Google Colab
Not Supported
LLaMA-Factory
Not Supported
Llama
Supported
Ludwig
Not Supported
Mistral AI
Supported
NVIDIA TensorRT
Supported
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Integrations
Dataoorts GPU Cloud
Supported
Gemini
Not Supported
Gemini Enterprise
Not Supported
GitHub
Supported
Google Colab
Supported
LLaMA-Factory
Supported
Llama
Not Supported
Ludwig
Supported
Mistral AI
Not Supported
NVIDIA TensorRT
Not Supported
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