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Qwen2 57B A14B Instruct GPTQ Int4 MLX by zhaokai

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  Autotrain compatible   Conversational   Endpoints compatible   Gptq   Instruct   Quantized   Qwen2 moe   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/zhaokai/Qwen2-57B-A14B-Instruct-GPTQ-Int4-MLX 

Qwen2 57B A14B Instruct GPTQ Int4 MLX Benchmarks

LLME Score: 0.15745
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Qwen2 57B A14B Instruct GPTQ Int4 MLX (zhaokai/Qwen2-57B-A14B-Instruct-GPTQ-Int4-MLX)
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Qwen2 57B A14B Instruct GPTQ Int4 MLX Parameters and Internals

LLM NameQwen2 57B A14B Instruct GPTQ Int4 MLX
Repository 🤗https://huggingface.co/zhaokai/Qwen2-57B-A14B-Instruct-GPTQ-Int4-MLX 
Model Size57b
Required VRAM32.3 GB
Updated2024-08-30
Maintainerzhaokai
Model Typeqwen2_moe
Instruction-BasedYes
Model Files  5.2 GB: 1-of-7   5.3 GB: 2-of-7   5.2 GB: 3-of-7   5.3 GB: 4-of-7   5.3 GB: 5-of-7   5.2 GB: 6-of-7   0.8 GB: 7-of-7
GPTQ QuantizationYes
Quantization Typegptq
Model ArchitectureQwen2MoeForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.40.1
Tokenizer ClassQwen2Tokenizer
Padding Token<|endoftext|>
Vocabulary Size151936
Torch Data Typebfloat16
Errorsreplace

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Note: green Score (e.g. "73.2") means that the model is better than zhaokai/Qwen2-57B-A14B-Instruct-GPTQ-Int4-MLX.

Rank the Qwen2 57B A14B Instruct GPTQ Int4 MLX 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 v20241124
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