Dolphin is an innovative platform designed for video interaction leveraging large language models (LLMs). Whether you’re working on video understanding, processing, or generation, Dolphin has the functionalities you need. In this article, we will provide a step-by-step guide on how to get started with Dolphin and troubleshoot common issues that may arise.

Getting Started with Dolphin

Follow these steps to prepare your environment and start using the Dolphin platform:

1. Set Up Your Environment

• It’s best to use conda to manage your environment. Make sure to use Python 3.8:

conda create -n dolphin python=3.8
conda activate dolphin

2. Clone the Repository

• Now, clone the Dolphin repository:

git clone https://github.com/BUAA-PrismGroup/dolphin.git
cd dolphin

3. Install Dependencies

• Install the necessary dependencies with the following command:

pip install -r requirements.txt

Running Dolphin

To start Dolphin, you can specify GPU/CPU assignments while loading the necessary models. This involves determining which Video Foundation Model to use. Models and devices are separated by underscores (_), while different models are separated by commas (,).

Sample Commands

• For CPU Users:

python video_chatgpt.py --load VideoCaptioning_cpu,ImageCaptioning_cpu,ModelscopeT2V_cpu

• For GPU Users (e.g., with 4 Tesla V100 32GB):

python video_chatgpt.py

Ensure you check the GPU memory usage table provided in the documentation to manage resource allocation effectively.

Expanding Dolphin’s Capabilities

Dolphin’s framework is designed to be extensible for adding new features and models. If you want to add a new video foundation model, follow these steps:

Adding a New Model

• Create a new package within the modules directory.
• Implement a class with initialization and inference functions.
• Update the configs/backends.yaml file with the new model information.

This approach ensures that Dolphin remains flexible and up to date with the latest advancements in video interaction technology.

Troubleshooting Common Issues

Should you encounter issues while using Dolphin, here are some common troubleshooting ideas:

• Ensure all dependencies are installed correctly by rerunning pip install -r requirements.txt.
• If you experience resource allocation issues, refer to the GPU memory usage table to optimize your model loading.
• No output received? Validate the configuration in configs/backends.yaml and make necessary adjustments.

For more insights, updates, or to collaborate on AI development projects, stay connected with fxis.ai.

Conclusion

With Dolphin, you have access to a powerful tool for video interaction. By following the steps outlined in this guide, you can set up your project, run the platform, and even extend its capabilities. At fxis.ai, we believe that such advancements are crucial for the future of AI, as they enable more comprehensive and effective solutions. Our team is continually exploring new methodologies to push the envelope in artificial intelligence, ensuring that our clients benefit from the latest technological innovations.