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Deepseek Math 7B Instruct AWQ Q4 by hanspeterlyngsoeraaschoujensen

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Deepseek Math 7B Instruct AWQ Q4 is an open-source language model by hanspeterlyngsoeraaschoujensen. Features: 7b LLM, VRAM: 4.8GB, Context: 4K, Quantized, Instruction-Based, HF Score: 51, LLM Explorer Score: 0.14, Arc: 53.4, HellaSwag: 71.5, MMLU: 56, TruthfulQA: 40.2, WinoGrande: 65.8, GSM8K: 19.4.

  4-bit   Awq   Conversational   Endpoints compatible   Instruct   Llama   Q4   Quantized   Region:us   Safetensors
Model Card on HF 🤗: https://huggingface.co/hanspeterlyngsoeraaschoujensen/deepseek-math-7b-instruct-awq-Q4 

Deepseek Math 7B Instruct AWQ Q4 Benchmarks

ARC: 53.41 vs 96.7 (so35)-44.8%
HellaSwag: 71.5 vs 95.3 (gpt4)-25%
MMLU: 55.97 vs 88.3 (so35)-36.6%
TruthfulQA: 40.16 vs 59 (gpt4)-31.9%
WinoGrande: 65.75 vs 87.5 (gpt4)-24.9%
GSM8K: 19.41 vs 96.4 (so35)-79.9%
LLME Score: 0.14432
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Deepseek Math 7B Instruct AWQ Q4 (hanspeterlyngsoeraaschoujensen/deepseek-math-7b-instruct-awq-Q4)
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Deepseek Math 7B Instruct AWQ Q4 Parameters and Internals

LLM NameDeepseek Math 7B Instruct AWQ Q4
Repository 🤗https://huggingface.co/hanspeterlyngsoeraaschoujensen/deepseek-math-7b-instruct-awq-Q4 
Base Model(s)  Deepseek Math 7B Instruct   deepseek-ai/deepseek-math-7b-instruct
Model Size7b
Required VRAM4.8 GB
Updated2026-03-29
Maintainerhanspeterlyngsoeraaschoujensen
Model Typellama
Instruction-BasedYes
Model Files  4.8 GB
AWQ QuantizationYes
Quantization Typeawq|q4
Model ArchitectureLlamaForCausalLM
Context Length4096
Model Max Length4096
Transformers Version4.37.2
Tokenizer ClassLlamaTokenizer
Vocabulary Size102400
Torch Data Typefloat16

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Instruction Following and Task Automation  
Factuality and Completeness of Knowledge  
Censorship and Alignment  
Data Analysis and Insight Generation  
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