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Napoleon 24B V0.0 by baconnier

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Napoleon 24B V0.0 is an open-source language model by baconnier. Features: 24b LLM, VRAM: 47.3GB, Context: 32K, Quantized, Instruction-Based, LLM Explorer Score: 0.25.

  Arxiv:1910.09700   4bit   Conversational   Endpoints compatible   Instruct   Mistral   Quantized   Region:us   Safetensors   Sharded   Tensorflow   Unsloth
Model Card on HF 🤗: https://huggingface.co/baconnier/Napoleon_24B_V0.0 

Napoleon 24B V0.0 Benchmarks

LLME Score: 0.25283
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Napoleon 24B V0.0 (baconnier/Napoleon_24B_V0.0)
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Napoleon 24B V0.0 Parameters and Internals

LLM NameNapoleon 24B V0.0
Repository 🤗https://huggingface.co/baconnier/Napoleon_24B_V0.0 
Model Size24b
Required VRAM47.3 GB
Updated2026-05-22
Maintainerbaconnier
Model Typemistral
Instruction-BasedYes
Model Files  4.8 GB: 1-of-10   4.8 GB: 2-of-10   4.8 GB: 3-of-10   4.9 GB: 4-of-10   4.8 GB: 5-of-10   4.8 GB: 6-of-10   4.9 GB: 7-of-10   4.8 GB: 8-of-10   4.8 GB: 9-of-10   3.9 GB: 10-of-10
Quantization Type4bit
Model ArchitectureMistralForCausalLM
Context Length32768
Model Max Length32768
Transformers Version4.48.3
Tokenizer ClassLlamaTokenizer
Padding Token<pad>
Vocabulary Size131072
Torch Data Typebfloat16

Best Alternatives to Napoleon 24B V0.0

Best Alternatives
Context / RAM
Downloads
Likes
...al Small 2507 Unsloth Bnb 4bit128K / 15 GB2115
...al Small 2506 Unsloth Bnb 4bit40K / 15 GB374
Not So Small Alpaca 24B32K / 47.3 GB140
...Instruct 2501 Unsloth Bnb 4bit32K / 15 GB295519
...all 24B Instruct 2501 Bnb 4bit32K / 14.2 GB16133
...b With Nemotron Converted Vllm32K / 47.3 GB380
...24B Base 2501 Unsloth Bnb 4bit32K / 15.7 GB2333
...ral Small 24B New Params 16bit32K / 47.3 GB50
...l Small 24B Base 2501 Bnb 4bit32K / 14.2 GB292
...ral Nemo Instruct 24B Merge V11000K / 24.6 GB90
Note: green Score (e.g. "73.2") means that the model is better than baconnier/Napoleon_24B_V0.0.

Rank the Napoleon 24B V0.0 Capabilities

🆘 Have you tried this model? Rate its performance. This feedback would greatly assist ML community in identifying the most suitable model for their needs. Your contribution really does make a difference! 🌟

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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