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Qwen2 VL 7B Instruct GPTQ Int4 by Qwen

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Qwen2 VL 7B Instruct GPTQ Int4 is an open-source language model by Qwen. Features: 7b LLM, VRAM: 7GB, Context: 32K, License: apache-2.0, Quantized, Instruction-Based, LLM Explorer Score: 0.18.

  4-bit Base model:quantized:qwen/qwen... Base model:qwen/qwen2-vl-7b-in...   En   Gptq   Image-text-to-text   Instruct   Multimodal   Quantized   Qwen2 vl   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/Qwen/Qwen2-VL-7B-Instruct-GPTQ-Int4 

Qwen2 VL 7B Instruct GPTQ Int4 Benchmarks

LLME Score: 0.17867
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Qwen2 VL 7B Instruct GPTQ Int4 (Qwen/Qwen2-VL-7B-Instruct-GPTQ-Int4)
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Qwen2 VL 7B Instruct GPTQ Int4 Parameters and Internals

Model Type 
multimodal, text generation
Use Cases 
Areas:
Research, Commercial applications
Applications:
Visual understanding, Video-based question answering, Mobile device operation, Multilingual text understanding
Primary Use Cases:
Image and video processing, Complex task automation, Multilingual text recognition
Limitations:
Does not understand audio, Data timeliness limited to June 2023, Limited in recognizing individuals or IPs, Needs improved capability for complex instructions, Accuracy issues in object counting, Weak in 3D spatial reasoning
Supported Languages 
English (fluent), Chinese (fluent), European languages (basic), Japanese (basic), Korean (basic), Arabic (basic), Vietnamese (basic)
Training Details 
Data Sources:
Image datasets updated until June 2023
Model Architecture:
Naive Dynamic Resolution, Multimodal Rotary Position Embedding (M-ROPE)
Input Output 
Input Format:
Images, Videos, Text
Accepted Modalities:
Image, Video, Text
Output Format:
Text
Performance Tips:
Enable flash_attention_2 for better acceleration and memory saving, especially in multi-image and video scenarios.
LLM NameQwen2 VL 7B Instruct GPTQ Int4
Repository 🤗https://huggingface.co/Qwen/Qwen2-VL-7B-Instruct-GPTQ-Int4 
Base Model(s)  Qwen2 VL 7B Instruct   Qwen/Qwen2-VL-7B-Instruct
Model Size7b
Required VRAM7 GB
Updated2024-09-08
MaintainerQwen
Model Typeqwen2_vl
Instruction-BasedYes
Model Files  4.0 GB: 1-of-2   3.0 GB: 2-of-2
Supported Languagesen
GPTQ QuantizationYes
Quantization Typegptq
Model ArchitectureQwen2VLForConditionalGeneration
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.45.0.dev0
Tokenizer ClassQwen2Tokenizer
Padding Token<|endoftext|>
Vocabulary Size152064
Torch Data Typefloat16
Errorsreplace

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Note: green Score (e.g. "73.2") means that the model is better than Qwen/Qwen2-VL-7B-Instruct-GPTQ-Int4.

Rank the Qwen2 VL 7B Instruct GPTQ Int4 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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