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Llama 2 7B by meta-llama

 »  All LLMs  »  meta-llama  »  Llama 2 7B   URL Share it on

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  Arxiv:2307.09288   En   Facebook   Llama   Llama2   Meta   Pytorch   Region:us
Model Card on HF 🤗: https://huggingface.co/meta-llama/Llama-2-7b 

Llama 2 7B Benchmarks

LLME Score: 0.19527
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Llama 2 7B (meta-llama/Llama-2-7b)
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Llama 2 7B Parameters and Internals

Model Type 
Text Generation
Use Cases 
Areas:
Commercial, Research
Limitations:
Use in languages other than English, Use violating laws or the Acceptable Use Policy
Considerations:
Developers should follow the Responsible Use Guide.
Additional Notes 
Future versions will be released with improvements based on community feedback.
Supported Languages 
English (High Proficiency), Other Languages (Not supported)
Training Details 
Data Sources:
Publicly available online data
Data Volume:
2 trillion tokens
Methodology:
Pretrained and fine-tuned using SFT and RLHF
Context Length:
4000
Hardware Used:
A100-80GB GPUs
Model Architecture:
Transformer
Safety Evaluation 
Methodologies:
Evaluation on safety datasets like TruthfulQA and Toxigen
Findings:
The model carries risks of producing inaccurate or biased outputs.
Risk Categories:
Inaccurate Responses, Biased Outputs, Objectionable Responses
Ethical Considerations:
Developers should perform tailored safety testing before deployment.
Input Output 
Input Format:
Text
Accepted Modalities:
Text
Output Format:
Text
Performance Tips:
Specific formatting needed for expected features, including INST and <> tags.
LLM NameLlama 2 7B
Repository 🤗https://huggingface.co/meta-llama/Llama-2-7b 
Model Size7b
Updated2025-07-26
Maintainermeta-llama
Supported Languagesen
Model ArchitectureMambaSSM
Licensellama2
Vocabulary Size-1

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Note: green Score (e.g. "73.2") means that the model is better than meta-llama/Llama-2-7b.

Rank the Llama 2 7B 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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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241124
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