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Qwen2.5 7B Instruct GPTQ Int8 by Qwen

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  Arxiv:2309.00071   Arxiv:2407.10671   8-bit   Autotrain compatible Base model:quantized:qwen/qwen... Base model:qwen/qwen2.5-7b-ins...   Chat   Conversational   En   Endpoints compatible   Gptq   Instruct   Quantized   Qwen2   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/Qwen/Qwen2.5-7B-Instruct-GPTQ-Int8 

Qwen2.5 7B Instruct GPTQ Int8 Benchmarks

LLME Score: 0.23202
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Qwen2.5 7B Instruct GPTQ Int8 (Qwen/Qwen2.5-7B-Instruct-GPTQ-Int8)
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Qwen2.5 7B Instruct GPTQ Int8 Parameters and Internals

Model Type 
causal language model
Use Cases 
Areas:
Research, Commercial applications
Applications:
Natural language processing, Coding, Mathematics, Chatbots
Primary Use Cases:
Generating long texts, Understanding structured data, Multilingual text processing
Supported Languages 
languages_supported (29 languages including Chinese, English, French, Spanish, Portuguese, German, Italian, Russian, Japanese, Korean, Vietnamese, Thai, Arabic, and more), proficiency (Multilingual support)
Training Details 
Data Sources:
various sources mentioned in the technical report
Methodology:
Pretraining & Post-training
Context Length:
131072
Model Architecture:
transformers with RoPE, SwiGLU, RMSNorm, and Attention QKV bias
Input Output 
Input Format:
Chat-based structured prompts
Accepted Modalities:
text
Output Format:
Generated text following the prompt schema with a max of 8192 tokens
Performance Tips:
Use vLLM for processing long texts; ensure proper configuration of rope scaling for long contexts
LLM NameQwen2.5 7B Instruct GPTQ Int8
Repository 🤗https://huggingface.co/Qwen/Qwen2.5-7B-Instruct-GPTQ-Int8 
Base Model(s)  Qwen/Qwen2.5-7B-Instruct   Qwen/Qwen2.5-7B-Instruct
Model Size7b
Required VRAM8.9 GB
Updated2025-09-23
MaintainerQwen
Model Typeqwen2
Instruction-BasedYes
Model Files  4.0 GB: 1-of-3   3.8 GB: 2-of-3   1.1 GB: 3-of-3
Supported Languagesen
GPTQ QuantizationYes
Quantization Typegptq
Model ArchitectureQwen2ForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.39.3
Tokenizer ClassQwen2Tokenizer
Padding Token<|endoftext|>
Vocabulary Size152064
Torch Data Typefloat16
Errorsreplace

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Qwen2.5 7B Instruct GPTQ Int432K / 5.6 GB25462128
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Qwen2.5 7B Instruct 1M 4bit986K / 4.3 GB113710
...B Instruct 1M Unsloth Bnb 4bit986K / 7.5 GB773
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Qwen2.5 7B Instruct 1M 6bit986K / 6.2 GB102
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Note: green Score (e.g. "73.2") means that the model is better than Qwen/Qwen2.5-7B-Instruct-GPTQ-Int8.

Rank the Qwen2.5 7B Instruct GPTQ Int8 Capabilities

🆘 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! 🌟

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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Release v20241124
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