With DeepSeek-VL, experience a step towards authentic vision-language understanding using a highly diverse and scalable open-source model. Its design is aimed at real-world applications, parsing content from various media like web screenshots and OCR.

• It uses a taxonomy based on real user scenarios for instruction tuning.
• It incorporates a hybrid vision encoder to efficiently process high-resolution images.
• The training strategy ensures strong language capabilities are retained.
• The model has shown state-of-the-art performance in vision-language chatbot applications.

DeepSeek-VL’s focus on real-world applicability and efficiency may result in more practical and accessible solutions for vision-language tasks. The inclusion of robust language capabilities can potentially prompt further interdisciplinary AI research. Access to both the 1.3B and 7B models can democratize advancements, encouraging the community to build upon this foundation.