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maestro

streamline the fine-tuning process for multimodal models: PaliGemma 2, Florence-2, and Qwen2.5-VL

autodistill-florence-2

Use Florence 2 to auto-label data for use in training fine-tuned object detection models.

autodistill-grounded-sam-2

Use Segment Anything 2, grounded with Florence-2, to auto-label data for use in training vision models.

multimodal-maestro

Visual Prompting for Large Multimodal Models (LMMs)

ecko-cli

ecko-cli is a simple CLI tool that streamlines the process of processing images in a directory, generating captions, and saving them as text files. Additionally, it provides functionalities to create a JSONL file from images in the directory you specify. Images will be captioned using the Microsoft Florence-2-large model and ONNX

wd-llm-caption

A Python base cli tool for caption images with WD series, Joy-caption-pre-alpha,meta Llama 3.2 Vision Instruct and Qwen2 VL Instruct models.

setofmark

Visual Prompting for Large Multimodal Models (LMMs)