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llava-small-OpenELM-AIMv2-0.6B
cpu4dream/llava-small-OpenELM-AIMv2-0.6B
llava-small-OpenELM-AIMv2-0.6B is a image-text-to-text model from cpu4dream. Use it for the image-text-to-text task on the model card, and read the license before you ship it in a product. The card lists the license as mit.
<center<span style="font-size:2em;"Tiny Llava 4 CPU 🐛</span</center
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1.2 GB
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At a glance
- Task
- Image-Text-to-Text
- License
- mit
- Model type
- tinyllava
- Access
- Public
- Created
- Dec 17, 2024
- Updated
- Dec 18, 2024
- SHA
- d8d42cb6
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Model card
From the Hugging Face model README
<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 as the LLM backbone and AIMv2-Large-Patch14-224-distilled (309M) 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 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.
📊 Performance
| Model Name | VQAv2 | GQA | SQA | TextVQA | MM-VET | POPE | MME | MMMU |
|---|---|---|---|---|---|---|---|---|
| LLaVA-1.5-7B | 78.5 | 62.0 | 66.8 | 58.2 | 30.5 | 85.9 | 1510.7 | - |
| bczhou/TinyLLaVA-3.1B | 79.9 | 62.0 | 69.1 | 59.1 | 32.0 | 86.4 | 1464.9 | - |
| tinyllava/TinyLLaVA-Gemma-SigLIP-2.4B | 78.4 | 61.6 | 64.4 | 53.6 | 26.9 | 86.4 | 1339.0 | 31.7 |
| tinyllava/TinyLLaVA-Phi-2-SigLIP-3.1B | 80.1 | 62.1 | 73.0 | 60.3 | 37.5 | 87.2 | 1466.4 | 38.4 |
| cpu4dream/llava-small-OpenELM-AIMv2-0.6B | - | - | - | 39.68 | - | 83.93 | - | - |
🔗 References
- Task
- Image-Text-to-Text
- Type
- tinyllava
- License
- mit
- Languages
- en
- Created
- Dec 17, 2024
- Updated
- Dec 18, 2024