Welcome to the fascinating world of meme captioning! Our meme captioner model, based on the fine-tuned LLaVA-1.5-7B, is designed to generate concise descriptions of memes, capturing their essence, purpose, and target audience. In this guide, you’ll learn how to set up and utilize our model effectively.

Step 1: Clone the Repository

The first step to harnessing the power of our membrane captioner is to clone the repository. Open your terminal or command prompt and run the following command:

git clone https://github.com/AmirAbaskohi/Beyond-Words-A-Multimodal-Exploration-of-Persuasion-in-Memes.git

Step 2: Navigate to the LLaVA Folder

After cloning the repository, navigate to the LLaVA directory:

cd LLaVA

Step 3: Create a Conda Environment

Creating a conda environment helps us manage dependencies efficiently. Execute the following commands to set it up:

conda create -n llava_captioner python=3.10 -y
conda activate llava_captioner

Step 4: Install Required Packages

Now it’s time to install the necessary packages to ensure our model runs smoothly:

pip3 install -e .
pip3 install transformers==4.31.0
pip3 install protobuf

Step 5: Running the Model

Once everything is set up, you can interact with the model through the Command Line Interface (CLI). Use the command below, making sure to replace PATH_TO_IMAGE_FILE with the path to your meme image:

python3 -m llava.serve.cli --model-path AmirHossein1378/LLaVA-1.5-7b-meme-captioner --image-file PATH_TO_IMAGE_FILE

Understanding the Output

Upon running the model, it will produce a concise description that outlines the meme’s purpose and its intended audience, rather than the text that appears within the meme. Think of it as a tour guide summarizing the highlights of an art exhibit without actually reproducing the artwork itself.

Troubleshooting Common Issues

If you encounter errors or unexpected behavior while using the meme captioner model, consider the following troubleshooting tips:

• Environment Issues: Ensure that your Conda environment is correctly activated before installing or running the model.
• Dependency Conflicts: Double-check that all required packages were installed correctly. You may need to reinstall some packages.
• Model Path Errors: Verify the model path specified in your command is correct. Typos can lead to frustrating errors.

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

For More Information

For additional documentation, please refer to our GitHub repository.

Conclusion

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.