Mistral NeMo Minitron 8B Base by nvidia

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  Arxiv:2009.03300   Arxiv:2407.14679   Arxiv:2408.11796   Autotrain compatible   Endpoints compatible   Mistral   Nemo   Region:us   Safetensors   Sharded   Tensorflow

Mistral NeMo Minitron 8B Base 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 Minitron 8B Base (nvidia/Mistral-NeMo-Minitron-8B-Base)

Mistral NeMo Minitron 8B Base Parameters and Internals

Model Type 
text-to-text, language model
Use Cases 
Areas:
research, commercial applications
Primary Use Cases:
natural language generation
Limitations:
May amplify societal biases and return toxic responses, Inaccurate or omitted key information in responses
Considerations:
Developers should work with internal teams to ensure the model meets industry and use case requirements.
Supported Languages 
English (high), multilingual (varied)
Training Details 
Data Sources:
webpages, dialogues, articles, legal documents, math texts, science literature, financial documents
Data Volume:
380 billion tokens
Methodology:
pruning and distillation
Context Length:
8000
Hardware Used:
NVIDIA A100
Model Architecture:
Transformer Decoder (Auto-Regressive Language Model)
Responsible Ai Considerations 
Fairness:
The model may reflect biases present in the training data.
Transparency:
Model architecture and training methodologies are described in the report.
Accountability:
Developers using the model should ensure it meets industry requirements and mitigates potential biases.
Mitigation Strategies:
Introduced QA and alignment style data for performance improvements.
Input Output 
Input Format:
String (1D)
Accepted Modalities:
text
Output Format:
String (1D)
Performance Tips:
Works well within 8k characters or less.
LLM NameMistral NeMo Minitron 8B Base
Repository ๐Ÿค—https://huggingface.co/nvidia/Mistral-NeMo-Minitron-8B-Base 
Model Size8b
Required VRAM16.8 GB
Updated2025-03-12
Maintainernvidia
Model Typemistral
Model Files  4.9 GB: 1-of-4   5.0 GB: 2-of-4   4.9 GB: 3-of-4   2.0 GB: 4-of-4
Model ArchitectureMistralForCausalLM
Licenseother
Context Length8192
Model Max Length8192
Transformers Version4.40.2
Tokenizer ClassPreTrainedTokenizerFast
Vocabulary Size131072
Torch Data Typebfloat16

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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 v20241227