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Mahou 1.3 Mistral Nemo 12B by flammenai

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Mahou 1.3 Mistral Nemo 12B is an open-source language model by flammenai. Features: 12b LLM, VRAM: 24.5GB, Context: 1000K, License: apache-2.0, Instruction-Based, LLM Explorer Score: 0.14.

Base model:finetune:mistralai/... Base model:mistralai/mistral-n...   Conversational Dataset:flammenai/flamemix-dpo...   Dataset:flammenai/mahoumix-v1   Endpoints compatible   Instruct   Mistral   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/flammenai/Mahou-1.3-mistral-nemo-12B 

Mahou 1.3 Mistral Nemo 12B Benchmarks

LLME Score: 0.14326
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Mahou 1.3 Mistral Nemo 12B (flammenai/Mahou-1.3-mistral-nemo-12B)
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Mahou 1.3 Mistral Nemo 12B Parameters and Internals

Model Type 
text generation, roleplay
Use Cases 
Primary Use Cases:
casual conversation, character roleplay
Additional Notes 
Uses SillyTavern settings for optimal performance, including ChatML for context and the use of Instruct Mode.
Training Details 
Data Sources:
flammenai/MahouMix-v1, flammenai/FlameMix-DPO-v1
Methodology:
ORPO finetuned
Hardware Used:
Google Colab A100
Input Output 
Input Format:
ChatML format
LLM NameMahou 1.3 Mistral Nemo 12B
Repository 🤗https://huggingface.co/flammenai/Mahou-1.3-mistral-nemo-12B 
Base Model(s)  Mistral Nemo Instruct 2407   mistralai/Mistral-Nemo-Instruct-2407
Model Size12b
Required VRAM24.5 GB
Updated2026-05-23
Maintainerflammenai
Model Typemistral
Instruction-BasedYes
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 Version4.43.3
Tokenizer ClassPreTrainedTokenizerFast
Vocabulary Size131072
Torch Data Typebfloat16

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Note: green Score (e.g. "73.2") means that the model is better than flammenai/Mahou-1.3-mistral-nemo-12B.

Rank the Mahou 1.3 Mistral Nemo 12B 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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