kosmos 2.5 chat

Introduction

Kosmos-2.5-Chat is a multimodal model developed by Microsoft, designed for machine reading of text-intensive images. It is particularly effective in Visual Question Answering (VQA) tasks. The model builds upon Kosmos-2.5, which is adept at generating spatially-aware text blocks and structured text outputs, formatted in Markdown.

Architecture

Kosmos-2.5 employs a shared decoder-only auto-regressive Transformer architecture. This framework supports the model's capability to generate text blocks with spatial coordinates and produce Markdown-style structured text. Task-specific prompts and flexible text representations enhance its performance in various multimodal tasks.

Training

Kosmos-2.5 was pre-trained on large-scale datasets of text-intensive images. Kosmos-2.5-Chat extends this with additional training focused on VQA tasks, making it suitable for real-world applications involving text-rich images. The model can adapt to different text-intensive image understanding tasks through supervised fine-tuning.

Guide: Running Locally

1. Environment Setup: Ensure you have Python installed. Clone the repository from GitHub.
2. Dependencies: Install required Python packages with pip install -r requirements.txt.
3. Running Inference: Use the script chat.py for document understanding tasks.
4. Hardware Requirements: For optimal performance, especially for VQA tasks, consider using cloud GPUs such as those offered by AWS or Google Cloud.

License

Kosmos-2.5-Chat is licensed under the MIT License. For more details, refer to the license file. The project adheres to the Microsoft Open Source Code of Conduct.