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NeonMaid 12B V2 by yamatazen

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NeonMaid 12B V2 is an open-source language model by yamatazen. Features: 12b LLM, VRAM: 23.8GB, Context: 128K, Merged, LLM Explorer Score: 0.2.

  Merged Model Base model:yamatazen/neonmaid-... Base model:yamatazen/orihime-g...   Chatml   Conversational   En   Endpoints compatible   Ja   Mistral   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/yamatazen/NeonMaid-12B-v2 

NeonMaid 12B V2 Benchmarks

LLME Score: 0.20169
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
NeonMaid 12B V2 (yamatazen/NeonMaid-12B-v2)
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NeonMaid 12B V2 Parameters and Internals

LLM NameNeonMaid 12B V2
Repository 🤗https://huggingface.co/yamatazen/NeonMaid-12B-v2 
Base Model(s)  NeonMaid 12B   Orihime Gutenberg 12B   yamatazen/NeonMaid-12B   yamatazen/Orihime-Gutenberg-12B
Merged ModelYes
Model Size12b
Required VRAM23.8 GB
Updated2026-04-10
Maintaineryamatazen
Model Typemistral
Model Files  1.3 GB: 1-of-25   1.3 GB: 2-of-25   1.0 GB: 3-of-25   0.9 GB: 4-of-25   0.9 GB: 5-of-25   0.9 GB: 6-of-25   1.0 GB: 7-of-25   0.9 GB: 8-of-25   0.9 GB: 9-of-25   0.9 GB: 10-of-25   1.0 GB: 11-of-25   0.9 GB: 12-of-25   0.9 GB: 13-of-25   0.9 GB: 14-of-25   1.0 GB: 15-of-25   0.9 GB: 16-of-25   0.9 GB: 17-of-25   0.9 GB: 18-of-25   1.0 GB: 19-of-25   0.9 GB: 20-of-25   0.9 GB: 21-of-25   0.9 GB: 22-of-25   1.0 GB: 23-of-25   0.9 GB: 24-of-25   0.8 GB: 25-of-25
Supported Languagesen ja
Model ArchitectureMistralForCausalLM
Context Length131072
Model Max Length131072
Transformers Version4.51.3
Tokenizer ClassPreTrainedTokenizer
Padding Token<pad>
Vocabulary Size131075
Torch Data Typebfloat16

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Note: green Score (e.g. "73.2") means that the model is better than yamatazen/NeonMaid-12B-v2.

Rank the NeonMaid 12B V2 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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