cpu4dream/llava-small-OpenELM-AIMv2-0.6B
<center><span style="font-size:2em;">Tiny Llava 4 CPU 🐛</span></center>
🚀 Model Overview
tiny-llava-open-elm-aimv2 is a lightweight image-text-to-text model that combines [OpenELM 270M - INSTRUCT](https://huggingface.co/apple/OpenELM-270M-Instruct) as the LLM backbone and [AIMv2-Large-Patch14-224-distilled (309M)](https://huggingface.co/apple/aimv2-large-patch14-224-distilled) as the vision encoder. The model has been fine-tuned using LoRA (Low-Rank Adaptation) for efficient training. It was developed using the [TinyLLaVA Factory](https://github.com/TinyLLaVA/TinyLLaVA_Factory) codebase, which provides a modular framework for lightweight multi-modal models.
The model is designed to run efficiently on CPU, making it ideal for resource-constrained environments. It is trained and evaluated on POPE and TextVQA benchmarks. The total model size is 0.6B parameters.