PaliGemma 2 mix
A vision-language model for multiple tasks
Listed in categories:
Artificial IntelligenceDeveloper Tools
Description
PaliGemma 2 mix is an advanced vision-language model designed for a variety of tasks, including image segmentation, video captioning, and question answering. It features pretrained checkpoints with different parameter sizes (3B, 10B, and 28B) that can be fine-tuned for specific applications, making it versatile and powerful for developers.
How to use PaliGemma 2 mix?
To use PaliGemma 2 mix, developers can explore its capabilities through a demo on Hugging Face, download model weights from Kaggle, and utilize Keras inference notebooks in Google Colab. Fine-tuning the model for specific tasks is recommended for optimal performance.
Core features of PaliGemma 2 mix:
1️⃣
Multiple task capabilities including captioning, OCR, and object detection
2️⃣
Developer-friendly model sizes (3B, 10B, 28B parameters)
3️⃣
Compatibility with popular frameworks like Hugging Face Transformers, Keras, and PyTorch
4️⃣
Easy upgrade from previous PaliGemma models
5️⃣
Comprehensive documentation and example notebooks for guidance
Why could be used PaliGemma 2 mix?
| # | Use case | Status | |
|---|---|---|---|
| # 1 | Image segmentation for visual content analysis | ✅ | |
| # 2 | Short and long video captioning for media applications | ✅ | |
| # 3 | Optical character recognition (OCR) for text extraction from images | ✅ | |
Who developed PaliGemma 2 mix?
PaliGemma is developed by Google, a leader in AI and machine learning technologies, known for its innovative solutions and commitment to advancing the field of artificial intelligence.