ColBERTFuture Data Systems
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Related Products
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About
Serve your ML model in any cloud in minutes. Unified model packaging format enabling both online and offline serving on any platform. 100x the throughput of your regular flask-based model server, thanks to our advanced micro-batching mechanism. Deliver high-quality prediction services that speak the DevOps language and integrate perfectly with common infrastructure tools. Unified format for deployment. High-performance model serving. DevOps best practices baked in. The service uses the BERT model trained with the TensorFlow framework to predict movie reviews' sentiment. DevOps-free BentoML workflow, from prediction service registry, deployment automation, to endpoint monitoring, all configured automatically for your team. A solid foundation for running serious ML workloads in production. Keep all your team's models, deployments, and changes highly visible and control access via SSO, RBAC, client authentication, and auditing logs.
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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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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
Companies, professionals and developers in search of a solution to simplify model deployment
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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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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 |
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Pricing
Free
Free Version
Free Trial
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Pricing
Free
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 InformationBentoML
United States
www.bentoml.com
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Company InformationFuture Data Systems
United States
github.com/stanford-futuredata/ColBERT
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Categories |
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Integrations
AWS Lambda
Amazon EC2
Amazon SageMaker
Amazon Web Services (AWS)
Apache Airflow
Apache Spark
Azure Container Registry
Docker
Google Compute Engine
Grafana Cloud
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Integrations
AWS Lambda
Amazon EC2
Amazon SageMaker
Amazon Web Services (AWS)
Apache Airflow
Apache Spark
Azure Container Registry
Docker
Google Compute Engine
Grafana Cloud
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