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Qwen2 72B Instruct by Qwen

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  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

MMLU Pro: 48.92
GPQA: 16.33
MUSR: 17.17
BBH: 57.48
IFEval: 79.89 vs 88 (so35)-9.2%
MATH Lvl 5: 37.69
LLME Score: 0.49026
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)

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
Updated2024-12-21
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 AWQ371779041 GB
Qwen2 72B Instruct GPTQ Int8141070877 GB
Qwen2 72B Instruct GPTQ Int431518641 GB
Qwen2 72B Instruct GGUF016813 GB
Qwen2 72B Instruct GGUF014513 GB
Qwen2 72B Instruct 4bit21540 GB

Best Alternatives to Qwen2 72B Instruct

Best Alternatives
Context / RAM
Downloads
Likes
EVA Qwen2.5 72B V0.2128K / 146 GB119210
...n2.5 72B 2x Instruct TIES V1.0128K / 146.1 GB221
72B Qwen2.5 Kunou V1128K / 146 GB53118
EVA Qwen2.5 72B V0.1128K / 146 GB65013
EVA Qwen2.5 72B V0.0128K / 146 GB1445
Athene V2 Chat32K / 146 GB7048244
Qwen2.5 72B Instruct32K / 145.5 GB269638615
Rombos LLM V2.5 Qwen 72B32K / 146.1 GB303130
Magnum V1 72B32K / 146 GB5569162
RYS XLarge32K / 156.3 GB279079
Note: green Score (e.g. "73.2") means that the model is better than Qwen/Qwen2-72B-Instruct.

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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Release v20241217
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