Florence-2-large - AI Vision Models Tool

Overview

Florence-2-large is a Microsoft vision foundation model for vision and vision-language tasks. It uses a prompt-based sequence-to-sequence transformer pretrained on the FLD-5B dataset and supports zero-shot and fine-tuned settings for tasks such as captioning, object detection, OCR, and segmentation.

Key Features

• Prompt-based sequence-to-sequence transformer architecture
• Pretrained on the FLD-5B dataset
• Supports zero-shot inference
• Supports fine-tuning for downstream tasks
• Handles image captioning
• Performs object detection
• Performs OCR extraction
• Supports image segmentation
• Designed as a vision foundation model

Ideal Use Cases

• Generate descriptive captions for images
• Detect and localize objects in images
• Extract text from scanned documents
• Produce segmentation masks for images
• Fine-tune for custom vision tasks

Getting Started

• Open the model page on Hugging Face: https://huggingface.co/microsoft/Florence-2-large
• Read the model card and available documentation
• Load the model into your preferred ML framework
• Run zero-shot prompts on sample images
• Fine-tune with a labeled dataset for specific tasks

Pricing

Pricing is not disclosed on the model page. Check Hugging Face or Microsoft for licensing and hosting costs.

Key Information

• Category: Vision Models
• Type: AI Vision Models Tool