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OmniLMM-12B
OmniLMM-12B is released at early time of this project. We recommond you to use our recently released models, for better performance and efficiency.
Archieve at: 2024-05-19
OmniLMM-12B is the most capable version. The model is built based on EVA02-5B and Zephyr-7B-β, connected with a perceiver resampler layer, and trained on multimodal data in a curriculum fashion. The model has three notable features:
🔥 Strong Performance.
OmniLMM-12B achieves leading performance among models with comparable sizes, surpassing established LMMs on multiple benchmarks (including MME, MMBench, SEED-Bench, etc). The model also endows rich multi-modal world knowledge.
🏆 Trustworthy Behavior.
LMMs are known for suffering from hallucination, often generating text that is not factually grounded in images (e.g., faithfully describing non-existing objects in images). OmniLMM-12B is the first state-of-the-art open-source LMM aligned via multimodal RLHF for trustworthy behavior (using the recent RLHF-V technique). It ranks #1 among open-source models on MMHal-Bench, and outperforms GPT-4V on Object HalBench.
🕹 Real-time Multimodal Interaction.
We combine the OmniLMM-12B and GPT-3.5 (text-only) into a real-time multimodal interactive assistant. The assistant accepts video streams from the camera and speech streams from the microphone and emits speech output. While still primary, we find the model can replicate some of the fun cases shown in the Gemini Demo video, without any video edition.
Evaluation
Click to view results on MME, MMBench, MMMU, MMBench, MMHal-Bench, Object HalBench, SeedBench, LLaVA Bench, MathVista.
Model | Size | MME | MMB dev (en) | MMMU val | MMHal-Bench | Object HalBench | SeedBench-I | MathVista | LLaVA Bench |
---|---|---|---|---|---|---|---|---|---|
GPT-4V† | - | 1771.5 | 75.1 | 56.8 | 3.53 / 70.8 | 86.4 / 92.7 | 71.6 | 47.8 | 93.1 |
Qwen-VL-Plus† | - | 2183.4 | 66.2 | 45.2 | - | - | 65.7 | 36.0 | 73.7 |
Yi-VL 6B | 6.7B | 1915.1 | 68.6 | 40.3 | - | - | 67.5 | 28.8 | 51.9 |
Qwen-VL-Chat | 9.6B | 1860.0 | 60.6 | 35.9 | 2.93 / 59.4 | 56.2 / 80.0 | 64.8 | 33.8 | 67.7 |
CogVLM-Chat | 17.4B | 1736.6 | 63.7 | 32.1 | 2.68 / 52.1 | 73.6 / 87.4 | 68.8 | 34.7 | 73.9 |
LLaVA 1.5 | 13.6B | 1808.4 | 68.2 | 36.4 | 2.71 / 51.0 | 53.7 / 77.4 | 68.1 | 26.4 | 64.6 |
OmniLMM-12B | 11.6B | 1935.8 | 71.6 | 40.7 | 3.45 / 68.8 | 90.3 / 95.5 | 71.1 | 34.9 | 72.0 |
Examples
We combine the OmniLMM-12B and GPT-3.5 (text-only) into a real-time multimodal interactive assistant. Video frames are described in text using OmniLMM-12B, and ChatGPT 3.5 (text-only) is employed to generate response according to the descriptions and user prompts. The demo video is a raw recording without edition.
Model Zoo
Model | Description | Download Link |
---|---|---|
OmniLMM-12B | The most capable version with leading performance. | 🤗 |