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Smaug Mixtral V0.1 by abacusai

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Smaug Mixtral V0.1 is an open-source language model by abacusai. Features: 46.7b LLM, VRAM: 187.7GB, Context: 32K, License: apache-2.0, Fine-Tuned, LLM Explorer Score: 0.22, Arc: 74.7, HellaSwag: 87.7, MMLU: 70.1, GSM8K: 72.

  Arxiv:2402.13228   Conversational   Endpoints compatible   Finetuned   Mixtral   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/abacusai/Smaug-Mixtral-v0.1 

Smaug Mixtral V0.1 Benchmarks

ARC: 74.66 vs 96.7 (so35)-22.8%
HellaSwag: 87.72 vs 95.3 (gpt4)-8%
MMLU: 70.06 vs 88.3 (so35)-20.7%
GSM8K: 71.95 vs 96.4 (so35)-25.4%
LLME Score: 0.21935
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Smaug Mixtral V0.1 (abacusai/Smaug-Mixtral-v0.1)
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Smaug Mixtral V0.1 Parameters and Internals

Model Type 
finetune
Additional Notes 
This model is designed for low edit distance datasets, like math-based datasets, and performs well across diverse tasks due to the DPOP training technique.
Training Details 
Data Sources:
ARC, HellaSwag, MetaMath, other existing datasets
Methodology:
DPO-Positive (DPOP), pairwise preference versions
LLM NameSmaug Mixtral V0.1
Repository 🤗https://huggingface.co/abacusai/Smaug-Mixtral-v0.1 
Model Size46.7b
Required VRAM187.7 GB
Updated2025-12-23
Maintainerabacusai
Model Typemixtral
Model Files  4.9 GB: 1-of-39   4.9 GB: 2-of-39   4.9 GB: 3-of-39   4.9 GB: 4-of-39   4.9 GB: 5-of-39   4.9 GB: 6-of-39   4.9 GB: 7-of-39   4.9 GB: 8-of-39   4.9 GB: 9-of-39   4.9 GB: 10-of-39   4.9 GB: 11-of-39   5.0 GB: 12-of-39   4.8 GB: 13-of-39   4.9 GB: 14-of-39   4.9 GB: 15-of-39   4.9 GB: 16-of-39   4.9 GB: 17-of-39   4.9 GB: 18-of-39   4.9 GB: 19-of-39   4.9 GB: 20-of-39   4.9 GB: 21-of-39   4.9 GB: 22-of-39   4.9 GB: 23-of-39   4.9 GB: 24-of-39   4.9 GB: 25-of-39   4.9 GB: 26-of-39   4.9 GB: 27-of-39   4.9 GB: 28-of-39   4.9 GB: 29-of-39   4.9 GB: 30-of-39   4.9 GB: 31-of-39   4.9 GB: 32-of-39   4.9 GB: 33-of-39   4.9 GB: 34-of-39   4.9 GB: 35-of-39   4.9 GB: 36-of-39   5.0 GB: 37-of-39   4.8 GB: 38-of-39   1.5 GB: 39-of-39
Model ArchitectureMixtralForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.36.2
Tokenizer ClassLlamaTokenizer
Vocabulary Size32000
Torch Data Typefloat32

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Note: green Score (e.g. "73.2") means that the model is better than abacusai/Smaug-Mixtral-v0.1.

Rank the Smaug Mixtral V0.1 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  
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