VILA 7B by Efficient-Large-Model

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  Arxiv:2312.07533   Autotrain compatible   Endpoints compatible   Llava llama   Region:us   Safetensors   Sharded   Tensorflow   Vila   Vlm

VILA 7B Benchmarks

nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
VILA 7B (Efficient-Large-Model/VILA-7b)
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VILA 7B Parameters and Internals

Model Type 
Visual Language Model (VLM)
Use Cases 
Areas:
Research on large multimodal models and chatbots
Primary Use Cases:
Research in computer vision, natural language processing, machine learning, and artificial intelligence
Additional Notes 
VILA unveils capabilities such as multi-image reasoning, in-context learning, visual chain-of-thought, and better world knowledge.
Training Details 
Methodology:
Pretrained with interleaved image-text data at scale. Includes AWQ 4bit quantization through TinyChat framework.
Hardware Used:
Jetson Orin, Laptop
LLM NameVILA 7B
Repository ๐Ÿค—https://huggingface.co/Efficient-Large-Model/VILA-7b 
Model Size7b
Required VRAM14.1 GB
Updated2025-10-24
MaintainerEfficient-Large-Model
Model Typellava_llama
Model Files  4.9 GB: 1-of-3   5.0 GB: 2-of-3   4.2 GB: 3-of-3   0.0 GB
Model ArchitectureLlavaLlamaForCausalLM
Licensecc-by-nc-4.0
Context Length4096
Model Max Length4096
Transformers Version4.36.2
Tokenizer ClassLlamaTokenizer
Padding 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 Efficient-Large-Model/VILA-7b.

Rank the VILA 7B 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 v20241124