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Kosmos-2: Grounding Multimodal Large Language Models to the World. [paper] [dataset] [online demo hosted by HuggingFace] Aug 2023: We acknowledge ydshieh at HuggingFace for the online demo and the HuggingFace's transformers implementation.
We introduce Kosmos-2, a Multimodal Large Language Model (MLLM), enabling new capabilities of perceiving object descriptions (e.g., bounding boxes) and grounding text to the visual world.
Experience the AI Revolution with KOSMOS-2: Microsoft's Cutting-Edge Breakthrough for Real-Time Text, Images, Video & Sound Generation!Get ready to witness t...
29 cze 2023 · Według badań Kosmos-2 jest modelem językowym, który umożliwia nowe możliwości postrzegania opisów obiektów (np. ramek ograniczających) i łączenia tekstu ze światem wizualnym. Reprezentowani badacze odnoszą się do wyrażeń jako odsyłaczy w Markdown, tj. „rozpiętości tekstu”, gdzie opisy obiektów są sekwencjami tokenów ...
Microsoft’s Kosmos 2: Everything You Need to Know About the Future of Multimodal Ai. In this captivating presentation, we'll delve into the revolutionary world of Kosmos-2, an exceptional ...
5 lut 2024 · Kosmos-2 builds on Kosmos-1, which supports perceiving multimodal input and in-context learning. Kosmos-2 was trained using a web-scale dataset of grounded image-text pairs, known as the GrIT, which includes text spans and bounding boxes that link specific regions in an image to relevant text.
Kosmos-2.5 is a multimodal literate model for machine reading of text-intensive images. Pre-trained on large-scale text-intensive images, Kosmos-2.5 excels in two distinct yet cooperative transcription tasks: (1) generating spatially-aware text blocks, where each block of text is assigned its spatial coordinates within the image, and (2 ...
