Haplo-VL
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Haplo Model Card
This work presents a simple yet efficient method to construct a baseline for the native and end-to-end large multi-modal model in a single transformer. The proposed model demonstrates superior performance compared to other LMMs using one transformer and significantly narrows the performance gap with compositional LMMs.
Model date: Haplo models were trained in September 2024.
Paper or resources for more information: https://haplo-vl.github.io/
Performace
| Model | SEEDB | POPE | RWQA | MMB | MMStar | VQAv2 | GQA | SQA |
|---|---|---|---|---|---|---|---|---|
| Haplo-8B-672 | 75.1 | 88.6 | 61.4 | 73.6 | 57.2 | 81.0 | 65.5 | 95.3 |
| Haplo-8B-MI-672 | 75.5 | 88.2 | 62.0 | 75.0 | 57.6 | 80.7 | 65.0 | 94.4 |
Intended use
Primary intended uses: The primary use of Haplo is research on large multimodal models and chatbots.
Primary intended users: The primary intended users of the model are researchers and hobbyists in computer vision, natural language processing, machine learning, and artificial intelligence.
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