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Llama 2 13B Chat AWQ by TheBloke

 »  All LLMs  »  TheBloke  »  Llama 2 13B Chat AWQ   URL Share it on

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  Arxiv:2307.09288   4-bit   Autotrain compatible   Awq Base model:meta-llama/llama-2-... Base model:quantized:meta-llam...   Deploy:azure   En   Facebook   Llama   Llama2   Meta   Pytorch   Quantized   Region:us   Safetensors
Model Card on HF 🤗: https://huggingface.co/TheBloke/Llama-2-13B-chat-AWQ 

Llama 2 13B Chat AWQ Benchmarks

LLME Score: 0.11202
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Llama 2 13B Chat AWQ (TheBloke/Llama-2-13B-chat-AWQ)
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Llama 2 13B Chat AWQ Parameters and Internals

Model Type 
llama
Use Cases 
Areas:
commercial, research
Applications:
dialogue, natural language generation
Primary Use Cases:
assistant-like chat, natural language generation tasks
Limitations:
use only in English, avoid inappropriate legal applications
Considerations:
Use proper formatting for optimal feature extraction and performance.
Additional Notes 
AWQ models support efficient inference and faster execution. Compatible with vLLM and AutoAWQ.
Training Details 
Data Sources:
publicly available online data
Data Volume:
2.0T tokens
Methodology:
auto-regressive language model with transformer architecture, supervised fine-tuning (SFT), and reinforcement learning with human feedback (RLHF)
Context Length:
4096
Hardware Used:
A100-80GB GPUs (TDP of 350-400W)
Model Architecture:
Transformer
Safety Evaluation 
Methodologies:
truthfulQA, Toxigen benchmarks
Findings:
Llama-2-Chat models demonstrate high-performance in safety tests
Risk Categories:
misinformation, bias
Ethical Considerations:
Testing conducted to date has been in English and may not cover all scenarios. Potential for inaccurate or objectionable responses exists.
Responsible Ai Considerations 
Fairness:
Testing conducted to date has been in English. Model may exhibit bias.
Transparency:
Limited model transparency as it is fine-tuned and pretrained with human feedback.
Accountability:
Meta is accountable for the model's performance and outputs.
Mitigation Strategies:
Developers advised to perform safety testing and tuning tailored to applications.
Input Output 
Input Format:
Structured text with prompt template
Accepted Modalities:
text
Output Format:
Generated text
Performance Tips:
Use 'INST' for better performance in chat tasks.
LLM NameLlama 2 13B Chat AWQ
Repository 🤗https://huggingface.co/TheBloke/Llama-2-13B-chat-AWQ 
Model NameLlama 2 13B Chat
Model CreatorMeta Llama 2
Base Model(s)  Llama 2 13B Chat Hf   meta-llama/Llama-2-13b-chat-hf
Model Size13b
Required VRAM7.2 GB
Updated2025-11-30
MaintainerTheBloke
Model Typellama
Model Files  7.2 GB
Supported Languagesen
AWQ QuantizationYes
Quantization Typeawq
Model ArchitectureLlamaForCausalLM
Licensellama2
Context Length4096
Model Max Length4096
Transformers Version4.31.0.dev0
Tokenizer ClassLlamaTokenizer
Beginning of Sentence Token<s>
End of Sentence Token</s>
Unk Token<unk>
Vocabulary Size32000
Torch Data Typefloat16

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Note: green Score (e.g. "73.2") means that the model is better than TheBloke/Llama-2-13B-chat-AWQ.

Rank the Llama 2 13B Chat AWQ 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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Release v20241124
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