Qwen2 72B Instruct 3.5bpw H6 EXL2 by LoneStriker

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  Arxiv:2309.00071   Autotrain compatible   Chat   Conversational   En   Endpoints compatible   Exl2   Instruct   Quantized   Qwen2   Region:us   Safetensors   Sharded   Tensorflow

Qwen2 72B Instruct 3.5bpw H6 EXL2 Benchmarks

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 3.5bpw H6 EXL2 Parameters and Internals

Model Type 
text-generation, multimodal
Use Cases 
Areas:
Research, Commercial applications
Supported Languages 
English (high), Chinese (high)
Training Details 
Methodology:
Pretrained with a large amount of data followed by supervised finetuning and direct preference optimization.
Context Length:
131072
Model Architecture:
Transformer architecture with SwiGLU activation, attention QKV bias, group query attention, and an improved tokenizer adaptive to multiple natural languages and codes.
Input Output 
Input Format:
Structured prompts following a chat template
Accepted Modalities:
text
Output Format:
Generated text responses
Performance Tips:
Use rope_scaling for processing longer contexts when necessary
LLM NameQwen2 72B Instruct 3.5bpw H6 EXL2
Repository ๐Ÿค—https://huggingface.co/LoneStriker/Qwen2-72B-Instruct-3.5bpw-h6-exl2 
Model Size72b
Required VRAM34.3 GB
Updated2024-11-21
MaintainerLoneStriker
Model Typeqwen2
Instruction-BasedYes
Model Files  8.5 GB: 1-of-4   8.6 GB: 2-of-4   8.6 GB: 3-of-4   8.6 GB: 4-of-4
Supported Languagesen
Quantization Typeexl2
Model ArchitectureQwen2ForCausalLM
Licenseother
Context Length32768
Model Max Length32768
Transformers Version4.40.1
Tokenizer ClassQwen2Tokenizer
Padding Token<|endoftext|>
Vocabulary Size152064
Torch Data Typebfloat16
Errorsreplace
Qwen2 72B Instruct 3.5bpw H6 EXL2 (LoneStriker/Qwen2-72B-Instruct-3.5bpw-h6-exl2)

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Note: green Score (e.g. "73.2") means that the model is better than LoneStriker/Qwen2-72B-Instruct-3.5bpw-h6-exl2.

Rank the Qwen2 72B Instruct 3.5bpw H6 EXL2 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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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241110