V Mllm 13B by VIM-Bench

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  Arxiv:2311.17647   Autotrain compatible   Endpoints compatible   Llava   Pytorch   Region:us   Sharded
Model Card on HF ๐Ÿค—: https://huggingface.co/VIM-Bench/v-mllm-13b 

V Mllm 13B Benchmarks

nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
V Mllm 13B (VIM-Bench/v-mllm-13b)

V Mllm 13B Parameters and Internals

Model Type 
multimodal, large language model
Use Cases 
Areas:
research
Training Details 
Data Sources:
VIM corpus based on LVIS-Instruct4V corpus
Data Volume:
846k
LLM NameV Mllm 13B
Repository ๐Ÿค—https://huggingface.co/VIM-Bench/v-mllm-13b 
Model Size13b
Required VRAM26.6 GB
Updated2025-02-05
MaintainerVIM-Bench
Model Typellava
Model Files  9.9 GB: 1-of-3   9.9 GB: 2-of-3   6.8 GB: 3-of-3   0.0 GB
Model ArchitectureLlavaLlamaForCausalLM
Licensellama2
Context Length4096
Model Max Length4096
Transformers Version4.31.0
Tokenizer ClassLlamaTokenizer
Beginning of Sentence Token<s>
End of Sentence Token</s>
Unk Token<unk>
Vocabulary Size32000
Torch Data Typebfloat16

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Note: green Score (e.g. "73.2") means that the model is better than VIM-Bench/v-mllm-13b.

Rank the V Mllm 13B Capabilities

๐Ÿ†˜ Have you tried this model? Rate its performance. This feedback would greatly assist ML community in identifying the most suitable model for their needs. Your contribution really does make a difference! ๐ŸŒŸ

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