DeepSeek-VL is an open-source Vision-Language (VL) Model designed for real-world vision and language understanding applications. Its approach is structured around three key dimensions. The tool ensures that its data is diverse, scalable, and extensively covers real-world scenarios, including web screenshots, PDFs, OCR, charts, and knowledge-based content, aiming for a comprehensive representation of practical contexts. Additionally, DeepSeek-VL creates a use case taxonomy from real user scenarios and constructs an instruction tuning dataset accordingly. This fine-tuning with the dataset substantially improves the model's user experience in practical applications.

Chat with DeepSeek-VL | An Open-Source Vision Language (VL) Model Designed for Real World

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Oliver George

DeepSeek-VL is an open-source Vision-Language (VL) Model designed for real-world vision and language understanding applications. Its approach is structured around three key dimensions. The tool ensures that its data is diverse, scalable, and extensively covers real-world scenarios, including web screenshots, PDFs, OCR, charts, and knowledge-based content, aiming for a comprehensive representation of practical contexts. Additionally, DeepSeek-VL creates a use case taxonomy from real user scenarios and constructs an instruction tuning dataset accordingly. This fine-tuning with the dataset substantially improves the model's user experience in practical applications.
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The AI language model, DeepSeek-VL 7B, is a powerful tool that has changed the way we communicate and generate content. With its advanced natural language processing capabilities, it can understand and respond to user input in a way that is both coherent and relevant. This makes it an invaluable asset for businesses and individuals alike who need assistance with writing or research tasks.

DeepSeek-VL Features
DeepSeek-VL Features
DeepSeek-VL, an open-source Vision-Language (VL) Model designed for real-world vision and language understanding applications.
Our approach is structured around three key dimensions:
  1. We strive to ensure our data is diverse, scalable, and extensively covers real-world scenarios including web screenshots, PDFs, OCR, charts, and knowledge-based content, aiming for a comprehensive representation of practical contexts.
  2. We create a use case taxonomy from real user scenarios and construct an instruction tuning dataset accordingly. The fine-tuning with this dataset substantially improves the model’s user experience in practical applications.
  3. Considering efficiency and the demands of most real-world scenarios, DeepSeek-VL incorporates a hybrid vision encoder that efficiently processes high-resolution images (1024 x 1024), while maintaining a relatively low computational overhead. This design choice ensures the model’s ability to capture critical semantic and detailed information across various visual tasks.
To ensure the preservation of LLM capabilities during pretraining, we investigate an effective VL pretraining strategy by integrating LLM training from the beginning and carefully managing the competitive dynamics observed between vision and language modalities.
The DeepSeek-VL family (both 1.3B and 7B models) showcases superior user experiences as a vision-language chatbot in real-world applications, achieving state-of-the-art or competitive performance across a wide range of visual-language benchmarks at the same model size while maintaining robust performance on language-centric benchmarks. We have made both 1.3B and 7B models publicly accessible to foster innovations based on this foundation model.

One of the key features of this AI language model is its ability to produce high-quality text that is engaging and informative. It has been trained on a large corpus of data, which enables it to generate responses that are accurate and relevant to the user’s query. Whether you need help with generating ideas, providing information, answering questions, or any other task, this AI language model can assist you.

Another important feature of this AI language model is its versatility. It can be used for a variety of purposes, including writing articles, creating content for websites and social media, generating marketing copy, and much more. Its wide range of applications make it a valuable tool for anyone who needs assistance with their writing or research tasks.

In addition to these features, this AI language model also has some unique capabilities that set it apart from other tools. For example, it can handle complex queries and provide detailed answers, even when the user’s question is not clear or specific. It can also adapt to different styles and tones, making it suitable for a wide range of audiences and contexts.

Furthermore, this AI language model allows users to customize its performance using various parameter settings such as Top-p, Temperature, Repetition penalty, Max Generation Tokens, Max History Tokens, and Select Models. These settings allow users to fine-tune the model’s behavior and achieve the desired output.

Overall, this AI language model is a powerful tool that can save time and effort while producing high-quality results. Whether you need assistance with writing or research, or simply want to generate engaging and informative content, this AI language model is here to help.

Oliver George
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