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Mistral Nemo Base 2407 Chatml by IntervitensInc

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Model Card on HF 🤗: https://huggingface.co/IntervitensInc/Mistral-Nemo-Base-2407-chatml 

Mistral Nemo Base 2407 Chatml Benchmarks

LLME Score: 0.17531
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Mistral Nemo Base 2407 Chatml (IntervitensInc/Mistral-Nemo-Base-2407-chatml)
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Mistral Nemo Base 2407 Chatml Parameters and Internals

Model Type 
generative text model
Use Cases 
Limitations:
No moderation mechanisms
Additional Notes 
Pretrained base model with no moderation mechanisms. Mistral Nemo requires smaller temperatures during use; recommended temperature is 0.3.
Supported Languages 
en (yes), fr (yes), de (yes), es (yes), it (yes), pt (yes), ru (yes), zh (yes), ja (yes)
Training Details 
Data Sources:
multilingual and code data
Context Length:
128000
Model Architecture:
Transformer - 40 layers, 5,120 dimensions, 32 heads, 128 head dim, 14,436 hidden dim, SwiGLU activation, 128k vocabulary, Rotary embeddings
LLM NameMistral Nemo Base 2407 Chatml
Repository 🤗https://huggingface.co/IntervitensInc/Mistral-Nemo-Base-2407-chatml 
Model Size12.2b
Required VRAM24.5 GB
Updated2025-09-23
MaintainerIntervitensInc
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
Supported Languagesen fr de es it pt ru zh ja
Model ArchitectureAutoModelForCausalLM
Licenseapache-2.0
Tokenizer ClassPreTrainedTokenizerFast
Vocabulary Size131072

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Rank the Mistral Nemo Base 2407 Chatml 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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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241124
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