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Midnight Rose 70B V2.0.3 AWQ by anyisalin

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Midnight Rose 70B V2.0.3 AWQ is an open-source language model by anyisalin. Features: 70b LLM, VRAM: 36.7GB, Context: 4K, Quantized, HF Score: 67.1, LLM Explorer Score: 0.14, Arc: 70.7, HellaSwag: 87.5, MMLU: 69.6, TruthfulQA: 65.3, WinoGrande: 81.2, GSM8K: 28.4.

  4-bit   Awq   Endpoints compatible   Llama   Quantized   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/anyisalin/Midnight-Rose-70B-v2.0.3-AWQ 

Midnight Rose 70B V2.0.3 AWQ Benchmarks

ARC: 70.65 vs 96.7 (so35)-26.9%
HellaSwag: 87.5 vs 95.3 (gpt4)-8.2%
MMLU: 69.64 vs 88.3 (so35)-21.1%
TruthfulQA: 65.27 vs 59 (gpt4)10.6%
WinoGrande: 81.22 vs 87.5 (gpt4)-7.2%
GSM8K: 28.35 vs 96.4 (so35)-70.6%
LLME Score: 0.14048
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Midnight Rose 70B V2.0.3 AWQ (anyisalin/Midnight-Rose-70B-v2.0.3-AWQ)
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Midnight Rose 70B V2.0.3 AWQ Parameters and Internals

LLM NameMidnight Rose 70B V2.0.3 AWQ
Repository 🤗https://huggingface.co/anyisalin/Midnight-Rose-70B-v2.0.3-AWQ 
Base Model(s)  sophosympatheia/Midnight-Rose-70B-v2.0.3   sophosympatheia/Midnight-Rose-70B-v2.0.3
Model Size70b
Required VRAM36.7 GB
Updated2026-03-29
Maintaineranyisalin
Model Typellama
Model Files  5.0 GB: 1-of-8   5.0 GB: 2-of-8   4.9 GB: 3-of-8   4.9 GB: 4-of-8   4.9 GB: 5-of-8   4.9 GB: 6-of-8   4.9 GB: 7-of-8   2.2 GB: 8-of-8
AWQ QuantizationYes
Quantization Typeawq
Model ArchitectureLlamaForCausalLM
Context Length4096
Model Max Length4096
Transformers Version4.38.2
Tokenizer ClassLlamaTokenizer
Padding Token<unk>
Vocabulary Size32000
Torch Data Typefloat16

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Note: green Score (e.g. "73.2") means that the model is better than anyisalin/Midnight-Rose-70B-v2.0.3-AWQ.

Rank the Midnight Rose 70B V2.0.3 AWQ 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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