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Mistral Nemo Gutenberg Doppel 12B V2 by nbeerbower

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  Autotrain compatible Base model:axolotl-ai-co/romul... Base model:finetune:axolotl-ai...   Conversational Dataset:jondurbin/gutenberg-dp... Dataset:nbeerbower/gutenberg2-...   Endpoints compatible   Mistral   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/nbeerbower/Mistral-Nemo-Gutenberg-Doppel-12B-v2 

Mistral Nemo Gutenberg Doppel 12B V2 Benchmarks

MMLU Pro: 28.29
GPQA: 2.8
MUSR: 13.05
BBH: 34.36
IFEval: 65.36 vs 88 (so35)-25.7%
MATH Lvl 5: 11.56
LLME Score: 0.27382
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Mistral Nemo Gutenberg Doppel 12B V2 (nbeerbower/Mistral-Nemo-Gutenberg-Doppel-12B-v2)
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Mistral Nemo Gutenberg Doppel 12B V2 Parameters and Internals

Training Details 
Data Sources:
jondurbin/gutenberg-dpo-v0.1, nbeerbower/gutenberg2-dpo
Methodology:
ORPO tuning
Hardware Used:
2x A100
LLM NameMistral Nemo Gutenberg Doppel 12B V2
Repository 🤗https://huggingface.co/nbeerbower/Mistral-Nemo-Gutenberg-Doppel-12B-v2 
Base Model(s)  Romulus Mistral Nemo 12B Simpo   axolotl-ai-co/romulus-mistral-nemo-12b-simpo
Model Size12b
Required VRAM24.5 GB
Updated2025-06-22
Maintainernbeerbower
Model Typemistral
Model Files  4.9 GB: 1-of-5   4.9 GB: 2-of-5   4.9 GB: 3-of-5   4.9 GB: 4-of-5   4.9 GB: 5-of-5
Model ArchitectureMistralForCausalLM
Licenseapache-2.0
Context Length1024000
Model Max Length1024000
Transformers Version4.45.1
Tokenizer ClassPreTrainedTokenizerFast
Padding Token<pad>
Vocabulary Size131072
Torch Data Typebfloat16

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Note: green Score (e.g. "73.2") means that the model is better than nbeerbower/Mistral-Nemo-Gutenberg-Doppel-12B-v2.

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Instruction Following and Task Automation  
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Release v20241124
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