Mistral Nemo Gutenberg 12B V3 by nbeerbower

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Mistral Nemo Gutenberg 12B V3 is an open-source language model by nbeerbower. Features: 12b LLM, VRAM: 24.5GB, Context: 1000K, License: apache-2.0, LLM Explorer Score: 0.2.

  Autotrain compatible Base model:finetune:interviten... Base model:intervitens/mini-ma...   Conversational Dataset:jondurbin/gutenberg-dp...   Endpoints compatible   Mistral   Model-index   Region:us   Safetensors   Sharded   Tensorflow

Mistral Nemo Gutenberg 12B V3 Benchmarks

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 12B V3 Parameters and Internals

Training Details 
Data Sources:
jondurbin/gutenberg-dpo-v0.1
Methodology:
Finetuned using an A100 on Google Colab for 3 epochs.
Hardware Used:
A100 on Google Colab
LLM NameMistral Nemo Gutenberg 12B V3
Repository 🤗https://huggingface.co/nbeerbower/mistral-nemo-gutenberg-12B-v3 
Base Model(s)  intervitens/mini-magnum-12b-v1.1   intervitens/mini-magnum-12b-v1.1
Model Size12b
Required VRAM24.5 GB
Updated2025-11-06
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 Version4.44.0
Tokenizer ClassPreTrainedTokenizerFast
Padding Token[PAD]
Vocabulary Size131073
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-12B-v3.

Rank the Mistral Nemo Gutenberg 12B V3 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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Release v20260328a