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Qwen2 72B Instruct by Qwen

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Qwen2 72B Instruct is an open-source language model by Qwen. Features: 72b LLM, VRAM: 145.5GB, Context: 32K, License: other, Instruction-Based, LLM Explorer Score: 0.49, ELO: 1261.

  Arxiv:2309.00071   Autotrain compatible Base model:finetune:qwen/qwen2...   Base model:qwen/qwen2-72b   Chat   Conversational   En   Endpoints compatible   Instruct   Qwen2   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/Qwen/Qwen2-72B-Instruct 

Qwen2 72B Instruct Benchmarks

LMSys ELO: 1261 vs 1272 (so35)-0.9%
MMLU Pro: 48.92
GPQA: 16.33
MUSR: 17.17
BBH: 57.48
IFEval: 79.89 vs 88 (so35)-9.2%
MATH Lvl 5: 41.77
LLME Score: 0.49442
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Qwen2 72B Instruct (Qwen/Qwen2-72B-Instruct)
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Qwen2 72B Instruct Parameters and Internals

Model Type 
text generation
Use Cases 
Areas:
chat
Applications:
text generation
Additional Notes 
Qwen2 models include an improved tokenizer adaptive to multiple natural languages and codes.
Supported Languages 
en (proficient), multiple natural languages (proficient)
Training Details 
Methodology:
Pretrained with a large amount of data, and post-trained with both supervised finetuning and direct preference optimization.
Context Length:
131072
Model Architecture:
Transformer architecture with SwiGLU activation, attention QKV bias, group query attention, etc.
Input Output 
Input Format:
Tokenized text
Accepted Modalities:
text
Output Format:
Generated text responses
Performance Tips:
Use vLLM for deployment to enhance performance on lengthy texts.
LLM NameQwen2 72B Instruct
Repository 🤗https://huggingface.co/Qwen/Qwen2-72B-Instruct 
Base Model(s)  Qwen2 72B   Qwen/Qwen2-72B
Model Size72b
Required VRAM145.5 GB
Updated2025-09-23
MaintainerQwen
Model Typeqwen2
Instruction-BasedYes
Model Files  3.8 GB: 1-of-37   4.0 GB: 2-of-37   3.8 GB: 3-of-37   4.0 GB: 4-of-37   4.0 GB: 5-of-37   4.0 GB: 6-of-37   3.8 GB: 7-of-37   4.0 GB: 8-of-37   4.0 GB: 9-of-37   4.0 GB: 10-of-37   3.8 GB: 11-of-37   4.0 GB: 12-of-37   4.0 GB: 13-of-37   4.0 GB: 14-of-37   3.8 GB: 15-of-37   4.0 GB: 16-of-37   4.0 GB: 17-of-37   4.0 GB: 18-of-37   3.8 GB: 19-of-37   4.0 GB: 20-of-37   4.0 GB: 21-of-37   4.0 GB: 22-of-37   3.8 GB: 23-of-37   4.0 GB: 24-of-37   4.0 GB: 25-of-37   4.0 GB: 26-of-37   3.8 GB: 27-of-37   4.0 GB: 28-of-37   4.0 GB: 29-of-37   4.0 GB: 30-of-37   3.8 GB: 31-of-37   4.0 GB: 32-of-37   4.0 GB: 33-of-37   4.0 GB: 34-of-37   3.8 GB: 35-of-37   4.0 GB: 36-of-37   3.5 GB: 37-of-37
Supported Languagesen
Model ArchitectureQwen2ForCausalLM
Licenseother
Context Length32768
Model Max Length32768
Transformers Version4.40.1
Tokenizer ClassQwen2Tokenizer
Padding Token<|endoftext|>
Vocabulary Size152064
Torch Data Typebfloat16
Errorsreplace

Quantized Models of the Qwen2 72B Instruct

Model
Likes
Downloads
VRAM
Qwen2 72B Instruct AWQ4142641 GB
Qwen2 72B Instruct GPTQ Int43318841 GB
Qwen2 72B Instruct GPTQ Int8155777 GB
Qwen2 72B Instruct GGUF05813 GB
Qwen2 72B Instruct GGUF05413 GB
Qwen2 72B Instruct 4bit21940 GB

Best Alternatives to Qwen2 72B Instruct

Best Alternatives
Context / RAM
Downloads
Likes
EVA Qwen2.5 72B V0.2128K / 146 GB18722
AceInstruct 72B128K / 146 GB26117
...n2.5 72B 2x Instruct TIES V1.0128K / 146.1 GB111
...2B PT BR Instruct Experimental128K / 146 GB80
... BI Qwen2.5 72B PT BR Instruct128K / 146 GB50
...A Abliterated TIES Qwen2.5 72B128K / 146.1 GB311
72B Qwen2.5 Kunou V1128K / 146 GB22624
EVA Qwen2.5 72B V0.1128K / 146 GB8119
EVA Qwen2.5 72B V0.0128K / 146 GB2255
Qwen2.5 72B Instruct32K / 145.5 GB683222922

Rank the Qwen2 72B Instruct 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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