ColBERTFuture Data Systems
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T5Google
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About
ColBERT is a fast and accurate retrieval model, enabling scalable BERT-based search over large text collections in tens of milliseconds. It relies on fine-grained contextual late interaction: it encodes each passage into a matrix of token-level embeddings. At search time, it embeds every query into another matrix and efficiently finds passages that contextually match the query using scalable vector-similarity (MaxSim) operators. These rich interactions allow ColBERT to surpass the quality of single-vector representation models while scaling efficiently to large corpora. The toolkit includes components for retrieval, reranking, evaluation, and response analysis, facilitating end-to-end workflows. ColBERT 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.
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About
With T5, we propose reframing all NLP tasks into a unified text-to-text-format where the input and output are always text strings, in contrast to BERT-style models that can only output either a class label or a span of the input. Our text-to-text framework allows us to use the same model, loss function, and hyperparameters on any NLP task, including machine translation, document summarization, question answering, and classification tasks (e.g., sentiment analysis). We can even apply T5 to regression tasks by training it to predict the string representation of a number instead of the number itself.
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Platforms Supported
Windows
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Mac
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Linux
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Cloud
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On-Premises
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iPhone
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iPad
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Android
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Chromebook
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Platforms Supported
Windows
Not Supported
Mac
Not Supported
Linux
Not Supported
Cloud
Supported
On-Premises
Supported
iPhone
Not Supported
iPad
Not Supported
Android
Not Supported
Chromebook
Not Supported
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Audience
Academic researchers and developers seeking a tool for implementing and evaluating listwise reranking with large language models
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Audience
AI developers interested in a powerful large language model
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Support
Phone Support
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24/7 Live Support
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Online
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Support
Phone Support
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24/7 Live Support
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Online
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API
Offers API
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API
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Screenshots and Videos |
Screenshots and VideosNo images available
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Pricing
Free
Free Version
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Free Trial
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Pricing
No information available.
Free Version
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Reviews/
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Training
Documentation
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Webinars
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Live Online
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In Person
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Training
Documentation
Supported
Webinars
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Live Online
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In Person
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Company InformationFuture Data Systems
United States
github.com/stanford-futuredata/ColBERT
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Company InformationGoogle
Founded: 1998
United States
ai.googleblog.com/2020/02/exploring-transfer-learning-with-t5.html
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Integrations
Medical LLM
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Spark NLP
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