Amazon Sagemaker
Amazon SageMaker is a fully-managed platform that enables developers and data scientists to quickly and easily build, train, and deploy machine learning models at any scale. With Amazon SageMaker, all the barriers and complexity that typically slow down developers who want to use machine learning are removed. The service includes models that can be used together or independently to build, train, and deploy your machine learning models.
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Upstage Document Parse
By:
Latest Version:
250116.2
Extract tables and figures from any document
Product Overview
Upstage Document Parse is a powerful API designed to automatically convert any document to HTML. It detects layout elements such as paragraphs, tables, images, equations, charts and more to determine the structure of the document. The API then serializes the elements according to reading order, and finally converts the document into HTML.
Key Data
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Type
Model Package
Highlights
Key Features
Text Recognition: Recognizes text through OCR or PDF parsing, excelling in English and CJK (Chinese, Japanese, Korean) documents, and provides PDF text extraction for digital-born PDFs. Layout Element Detection (LED): Detects layout elements like paragraphs, figures, tables, and captions, serializing them into human reading order, ideal for complex layouts. Table Structure Recognition (TSR): Converts complex tables to HTML, recognizing merged cells and tables with hidden gridlines.
Key Applications
The Upstage Document Parse model enhances LLM-based document processing and information retrieval by preserving contextual information better than traditional OCR. It is valuable for scenarios where LLMs process documents, integrating RAG with Layout Analysis via embedding techniques. It excels in information extraction and recognizing document structures across various templates without additional training, making it ideal for handling the same type of documents in different formats.
Key Tasks
- Document OCR
- Document Parsing
- Layout Analysis
- Information Extraction
- Layout Element Detection
- Table Structure Recognition
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Pricing Information
Use this tool to estimate the software and infrastructure costs based your configuration choices. Your usage and costs might be different from this estimate. They will be reflected on your monthly AWS billing reports.
Contact us to request contract pricing for this product.
Estimating your costs
Choose your region and launch option to see the pricing details. Then, modify the estimated price by choosing different instance types.
Version
Region
Software Pricing
Model Realtime Inference$15.00/hr
running on ml.g6.xlarge
Model Batch Transform$0.00/hr
running on ml.m5.12xlarge
Infrastructure PricingWith Amazon SageMaker, you pay only for what you use. Training and inference is billed by the second, with no minimum fees and no upfront commitments. Pricing within Amazon SageMaker is broken down by on-demand ML instances, ML storage, and fees for data processing in notebooks and inference instances.
Learn more about SageMaker pricing
With Amazon SageMaker, you pay only for what you use. Training and inference is billed by the second, with no minimum fees and no upfront commitments. Pricing within Amazon SageMaker is broken down by on-demand ML instances, ML storage, and fees for data processing in notebooks and inference instances.
Learn more about SageMaker pricing
SageMaker Realtime Inference$1.1267/host/hr
running on ml.g6.xlarge
SageMaker Batch Transform$2.765/host/hr
running on ml.m5.12xlarge
Model Realtime Inference
For model deployment as Real-time endpoint in Amazon SageMaker, the software is priced based on hourly pricing that can vary by instance type. Additional infrastructure cost, taxes or fees may apply.InstanceType | Realtime Inference/hr | |
---|---|---|
ml.g6.2xlarge | $15.00 | |
ml.g6.xlarge Vendor Recommended | $15.00 |
Usage Information
Model input and output details
Input
Summary
Provide input data in multipart form data View more detailed description here
Limitations for input type
Supported file formats: JPEG, PNG, BMP, PDF, TIFF, HEIC, DOCX, PPTX, XLSX
Maximum file size is 50MB.
Maximum number of pages per file is 100 pages. For files exceeding 100 pages, the first 100 pages are processed.
Input MIME type
image/jpeg, image/bmp, image/png, application/pdf, image/tiffSample input data
Output
Summary
https://developers.upstage.ai/docs/apis/document-parse#response-1 For detailed schema information, please click the 'Expand all output descriptions' button.
Output MIME type
application/jsonSample output data
Sample notebook
Additional Resources
End User License Agreement
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Support Information
Upstage Document Parse
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