Phi-3-V: Extending the Visual Capabilities of LLaVA with Phi-3

Repository Overview

This repository features LLaVA v1.5 trained with the Phi-3-mini-3.8B LLM. This integration aims to leverage the strengths of both models to offer advanced vision-language understanding.

Training Strategy

• Pretraining: Only Vision-to-Language projector is trained. The rest of the model is frozen.
• Fine-tuning: LLM is LoRA fine-tuned. Only the vision-backbone (CLIP) is kept frozen.
• Note: The repository contains merged weights.

Key Components

• Base Large Language Model (LLM): Phi-3-mini-4k-instruct
• Base Large Multimodal Model (LMM): LLaVA-v1.5

Training Data

• Pretraining Dataset: LCS-558K
• Fine-tuning Dataset: LLaVA-Instruct-665K

Download It As

git lfs install
git clone https://huggingface.co/MBZUAI/LLaVA-Phi-3-mini-4k-instruct

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License

This project is available under the MIT License.

Contributions

Contributions are welcome! Please 🌟 our repository LLaVA++ if you find this model useful.

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