Qwen2 VL 7B Instruct GPTQ Int8 by Qwen

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  Arxiv:2308.12966   Arxiv:2409.12191   8-bit Base model:quantized:qwen/qwen... Base model:qwen/qwen2-vl-7b-in...   Conversational   En   Gptq   Image-text-to-text   Instruct   Multimodal   Quantized   Qwen2 vl   Region:us   Safetensors   Sharded   Tensorflow

Qwen2 VL 7B Instruct GPTQ Int8 Benchmarks

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 Int8 (Qwen/Qwen2-VL-7B-Instruct-GPTQ-Int8)

Qwen2 VL 7B Instruct GPTQ Int8 Parameters and Internals

Model Type 
multimodal, text-generation
Use Cases 
Areas:
research, commercial applications
Applications:
visual understanding, video-based question answering, dialog, content creation
Primary Use Cases:
complex reasoning and decision making when integrated with devices
Limitations:
Lack of Audio Support, Data timeliness, Constraints in Individuals and IP, Limited Capacity for Complex Instruction, Insufficient Counting Accuracy, Weak Spatial Reasoning Skills
Supported Languages 
en (English), zh (Chinese), multi (most European languages, Japanese, Korean, Arabic, Vietnamese)
Input Output 
Accepted Modalities:
text, image, video
Output Format:
Generated response
Performance Tips:
Enable flash_attention_2 for better acceleration and memory saving.
LLM NameQwen2 VL 7B Instruct GPTQ Int8
Repository ๐Ÿค—https://huggingface.co/Qwen/Qwen2-VL-7B-Instruct-GPTQ-Int8 
Base Model(s)  Qwen2 VL 7B Instruct   Qwen/Qwen2-VL-7B-Instruct
Model Size7b
Required VRAM10.2 GB
Updated2025-02-18
MaintainerQwen
Model Typeqwen2_vl
Instruction-BasedYes
Model Files  4.0 GB: 1-of-3   4.0 GB: 2-of-3   2.2 GB: 3-of-3
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-Int8.

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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