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: All model parameters including LLM are fine-tuned. Only the vision-backbone (CLIP) is kept frozen.
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-FT
License
This project is available under the MIT License.
Contributions
Contributions are welcome! Please 🌟 our repository LLaVA++ if you find this model useful.