OmniLMM 12B by openbmb

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  Arxiv:2308.12038   Arxiv:2312.00849   Arxiv:2403.11703   Autotrain compatible Dataset:haoyezhang/rlhf-v-data...   Dataset:yirany/unimm-chat   Endpoints compatible   Omnilmm   Pytorch   Region:us   Visual-question-answering
Model Card on HF ๐Ÿค—: https://huggingface.co/openbmb/OmniLMM-12B 

OmniLMM 12B Benchmarks

nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
OmniLMM 12B (openbmb/OmniLMM-12B)

OmniLMM 12B Parameters and Internals

Model Type 
visual-question-answering
Use Cases 
Areas:
research, commercial applications
Primary Use Cases:
Real-time multimodal interaction
Training Details 
Data Sources:
HaoyeZhang/RLHF-V-Dataset, Yirany/UniMM-Chat
Methodology:
Trained on multimodal data in a curriculum fashion with a perceiver resampler layer.
Model Architecture:
Built based on EVA02-5B and Zephyr-7B-ฮฒ, and connected with a perceiver resampler layer.
LLM NameOmniLMM 12B
Repository ๐Ÿค—https://huggingface.co/openbmb/OmniLMM-12B 
Model Size12b
Required VRAM23.2 GB
Updated2025-02-22
Maintaineropenbmb
Model Typeomnilmm
Model Files  23.2 GB
Model ArchitectureOmniLMMForCausalLM
Context Length32768
Model Max Length32768
Transformers Version4.35.0
Tokenizer ClassLlamaTokenizer
Padding Token</s>
Vocabulary Size32009
Torch Data Typebfloat16

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Note: green Score (e.g. "73.2") means that the model is better than openbmb/OmniLMM-12B.

Rank the OmniLMM 12B Capabilities

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Instruction Following and Task Automation  
Factuality and Completeness of Knowledge  
Censorship and Alignment  
Data Analysis and Insight Generation  
Text Generation  
Text Summarization and Feature Extraction  
Code Generation  
Multi-Language Support and Translation  

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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241227