Explore a comprehensive tutorial on fine-tuning Google's open-source Vision-Language Model, PaliGemma, for custom object detection tasks. Follow step-by-step instructions to modify Google's notebook and train PaliGemma on a handwritten digits and math operations dataset from RF100. Dive into the JSONL format, learn how to deploy the fine-tuned model for real-world inference, and discover PaliGemma's capabilities in image captioning, visual question answering, and object detection. Gain insights into overcoming limitations and important considerations when working with this powerful model. Access additional resources, including GitHub repositories, research papers, and community sessions to further enhance your understanding and application of PaliGemma.
Overview
Syllabus
- PaliGemma Capabilities
- Environment Setup
- Dataset Format
- Downloading Pre-trained Model
- Loading Dataset
- Training and Evaluating the Model
- Deploying the Model
- Important Considerations
- Outro
- Community Session June 6th, 2024 at 08:00 AM PST / 11:00 AM EST / PM CET: https://roboflow.stream
Taught by
Roboflow
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