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Llama 2 7B Chat GGUF by TheBloke

 »  All LLMs  »  TheBloke  »  Llama 2 7B Chat GGUF   URL Share it on

  63927   
  Arxiv:2307.09288 Base model:meta-llama/llama-2-... Base model:quantized:meta-llam...   En   Facebook   Gguf   Llama   Llama2   Meta   Pytorch   Quantized   Region:us
Model Card on HF 🤗: https://huggingface.co/TheBloke/Llama-2-7B-Chat-GGUF 

Llama 2 7B Chat GGUF Benchmarks

LLME Score: 0.19001
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 Chat GGUF (TheBloke/Llama-2-7B-Chat-GGUF)
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Llama 2 7B Chat GGUF Parameters and Internals

Model Type 
text generation, dialogue
Use Cases 
Areas:
Commercial applications, Research
Primary Use Cases:
Assistant-like chat and dialogue
Limitations:
Unpredictable responses possible
Considerations:
Ensure safety testing and alignment to specific use.
Additional Notes 
Training and fine-tuning do not use Meta user data. Pretraining data cut off September 2022. Some tuning data up to July 2023.
Supported Languages 
en (high proficiency)
Training Details 
Data Sources:
A new mix of publicly available online data
Data Volume:
2.0 trillion tokens
Methodology:
Uses supervised fine-tuning (SFT) and reinforcement learning with human feedback (RLHF)
Context Length:
4096
Hardware Used:
Meta's Research Super Cluster and production clusters for pretraining, A100-80GB GPUs for a total of 3.3M GPU hours
Model Architecture:
Auto-regressive language model with optimized transformer architecture
Safety Evaluation 
Methodologies:
internal evaluations library
Findings:
Llama 2 7B scores well on TruthfulQA and presents low toxicity on ToxiGen
Risk Categories:
misinformation, bias
Ethical Considerations:
Model output may be unpredictable. Safety testing and tuning recommended before deployment.
Responsible Ai Considerations 
Fairness:
Testing conducted in English. May not cover all scenarios.
Transparency:
Details available in Responsible Use Guide on website.
Accountability:
Reports via given platforms
Mitigation Strategies:
Internal evaluations and updates
Input Output 
Input Format:
Text input with specific formatting.
Accepted Modalities:
text
Output Format:
Text generation
Performance Tips:
Use INST and <> tags for expected performance.
LLM NameLlama 2 7B Chat GGUF
Repository 🤗https://huggingface.co/TheBloke/Llama-2-7B-Chat-GGUF 
Model NameLlama 2 7B Chat
Model CreatorMeta Llama 2
Base Model(s)  Llama 2 7B Chat Hf   meta-llama/Llama-2-7b-chat-hf
Model Size7b
Required VRAM2.8 GB
Updated2025-08-24
MaintainerTheBloke
Model Typellama
Model Files  2.8 GB   3.6 GB   3.3 GB   3.0 GB   3.8 GB   4.1 GB   3.9 GB   4.7 GB   4.8 GB   4.7 GB   5.5 GB   7.2 GB
Supported Languagesen
GGUF QuantizationYes
Quantization Typegguf
Model ArchitectureAutoModel
Licensellama2

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Note: green Score (e.g. "73.2") means that the model is better than TheBloke/Llama-2-7B-Chat-GGUF.

Rank the Llama 2 7B Chat GGUF 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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