lucataco / llava-phi-3-mini

llava-phi-3-mini is a LLaVA model fine-tuned from microsoft/Phi-3-mini-4k-instruct

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Input

Output

Run time and cost

This model costs approximately $0.0034 to run on Replicate, or 294 runs per $1, but this varies depending on your inputs. It is also open source and you can run it on your own computer with Docker.

This model runs on Nvidia A40 GPU hardware. Predictions typically complete within 6 seconds.

Readme

llava-phi-3-mini

llava-phi-3-mini is a LLaVA model fine-tuned from microsoft/Phi-3-mini-4k-instruct and CLIP-ViT-Large-patch14-336 with ShareGPT4V-PT and InternVL-SFT by XTuner.

Note: This model is in HuggingFace LLaVA format.

Resources:

Details

Model Visual Encoder Projector Resolution Pretraining Strategy Fine-tuning Strategy Pretrain Dataset Fine-tune Dataset Pretrain Epoch Fine-tune Epoch
LLaVA-v1.5-7B CLIP-L MLP 336 Frozen LLM, Frozen ViT Full LLM, Frozen ViT LLaVA-PT (558K) LLaVA-Mix (665K) 1 1
LLaVA-Llama-3-8B CLIP-L MLP 336 Frozen LLM, Frozen ViT Full LLM, LoRA ViT LLaVA-PT (558K) LLaVA-Mix (665K) 1 1
LLaVA-Llama-3-8B-v1.1 CLIP-L MLP 336 Frozen LLM, Frozen ViT Full LLM, LoRA ViT ShareGPT4V-PT (1246K) InternVL-SFT (1268K) 1 1
LLaVA-Phi-3-mini CLIP-L MLP 336 Frozen LLM, Frozen ViT Full LLM, Full ViT ShareGPT4V-PT (1246K) InternVL-SFT (1268K) 1 2

Results

<div align="center"> Image </div>
Model MMBench Test (EN) MMMU Val SEED-IMG AI2D Test ScienceQA Test HallusionBench aAcc POPE GQA TextVQA MME MMStar
LLaVA-v1.5-7B 66.5 35.3 60.5 54.8 70.4 44.9 85.9 62.0 58.2 1511/348 30.3
LLaVA-Llama-3-8B 68.9 36.8 69.8 60.9 73.3 47.3 87.2 63.5 58.0 1506/295 38.2
LLaVA-Llama-3-8B-v1.1 72.3 37.1 70.1 70.0 72.9 47.7 86.4 62.6 59.0 1469/349 45.1
LLaVA-Phi-3-mini 69.2 41.4 70.0 69.3 73.7 49.8 87.3 61.5 57.8 1477/313 43.7

Reproduce

Please refer to docs.

Citation

@misc{2023xtuner,
    title={XTuner: A Toolkit for Efficiently Fine-tuning LLM},
    author={XTuner Contributors},
    howpublished = {\url{https://github.com/InternLM/xtuner}},
    year={2023}
}