kosmos-2.5 EU AI Act Compliance Profile

Kosmos-2.5

Microsoft Document AI | GitHub

Model description

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) producing structured text output that captures styles and structures into the markdown format. This unified multimodal literate capability is achieved through a shared decoder-only auto-regressive Transformer architecture, task-specific prompts, and flexible text representations. We evaluate Kosmos-2.5 on end-to-end document-level text recognition and image-to-markdown text generation. Furthermore, the model can be readily adapted for any text-intensive image understanding task with different prompts through supervised fine-tuning, making it a general-purpose tool for real-world applications involving text-rich images. This work also paves the way for the future scaling of multimodal large language models.

Kosmos-2.5: A Multimodal Literate Model

NOTE:

Since this is a generative model, there is a risk of hallucination during the generation process, and it CAN NOT guarantee the accuracy of all OCR/Markdown results in the images.

Inference

KOSMOS-2.5 is supported from Transformers >= 4.56. Find the docs here.

Markdown Task: For usage instructions, please refer to md.py.

import re
import torch
import requests
from PIL import Image, ImageDraw
from transformers import AutoProcessor, Kosmos2_5ForConditionalGeneration, infer_device

repo = "microsoft/kosmos-2.5"
device = "cuda:0"
dtype = torch.bfloat16
mod

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