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What is DeepSeek-VL?

DeepSeek-VL is a groundbreaking open-source model that merges vision and language capabilities, specifically designed for practical use in everyday settings. Our approach is based on three core principles: first, we emphasize the collection of a wide and scalable dataset that captures a variety of real-life situations, including web screenshots, PDFs, OCR outputs, charts, and knowledge-based data, to provide a comprehensive understanding of practical environments. Second, we create a taxonomy derived from genuine user scenarios and assemble a related instruction tuning dataset, which is aimed at boosting the model's performance. This fine-tuning process greatly enhances user satisfaction and effectiveness in real-world scenarios. Furthermore, to optimize efficiency while fulfilling the demands of common use cases, DeepSeek-VL includes a hybrid vision encoder that skillfully processes high-resolution images (1024 x 1024) without leading to excessive computational expenses. This thoughtful design not only improves overall performance but also broadens accessibility for a diverse group of users and applications, paving the way for innovative solutions in various fields. Ultimately, DeepSeek-VL represents a significant step towards bridging the gap between visual understanding and language processing.

What is DeepSeek-OCR?

DeepSeek-OCR is an innovative open-source framework designed to explore Contexts Optical Compression, striving to enhance the boundaries of visual-text compression while analyzing the function of vision encoders through the perspective of LLMs. This pioneering model adeptly compresses large contexts using optical 2D mapping, with DeepEncoder serving as its core engine and DeepSeek3B-MoE-A570M acting as the decoding component. By effectively maintaining low activations even with high-resolution inputs, DeepEncoder achieves remarkable compression ratios, facilitating a manageable number of vision tokens crucial for document comprehension. The framework is specifically optimized for optical character recognition (OCR) and document parsing tasks associated with images and PDFs, offering inference capabilities through either vLLM or Transformers. Users can efficiently perform image OCR with streaming outputs, manage PDFs with high concurrency, or carry out batch evaluations for benchmarking. Furthermore, DeepSeek-OCR can convert documents into Markdown format, providing the ability to conduct OCR without being limited by layout constraints, parsing figures, offering detailed descriptions of images, and identifying referenced text within images. This broad range of features not only enhances its functionality but also positions DeepSeek-OCR as an essential resource for individuals seeking sophisticated document processing solutions, making it a highly versatile tool in various applications. Additionally, its continuous evolution promises further enhancements in user experience and performance.

Media

Media

Integrations Supported

Python

Integrations Supported

DeepSeek
Markdown

API Availability

API Availability

Pricing Information

Free
Free Version

Pricing Information

Free
Free Version

Supported Platforms

SaaS

Supported Platforms

SaaS

Customer Service / Support

Standard Support
Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub
Online Training
On-Site Training

Training Options

Documentation Hub

Company Facts

Organization Name

DeepSeek

Date Founded

2023

Company Location

China

Company Website

www.deepseek.com

Company Facts

Organization Name

DeepSeek

Date Founded

2023

Company Location

China

Company Website

github.com/deepseek-ai/DeepSeek-OCR

Categories and Features

AI Vision Models

Not specified

Multimodal Models

Not specified

Categories and Features

AI Models

Not specified

OCR

Not specified

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