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Llama 2 7B Chat GPTQ by TheBloke

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Llama 2 7B Chat GPTQ is an open-source language model by TheBloke. Features: 7b LLM, VRAM: 3.9GB, Context: 4K, License: llama2, Quantized, LLM Explorer Score: 0.15.

  Arxiv:2307.09288   4-bit   Autotrain compatible Base model:meta-llama/llama-2-... Base model:quantized:meta-llam...   En   Facebook   Gptq   Llama   Llama2   Meta   Pytorch   Quantized   Region:us   Safetensors
Model Card on HF 🤗: https://huggingface.co/TheBloke/Llama-2-7B-Chat-GPTQ 

Llama 2 7B Chat GPTQ Benchmarks

LLME Score: 0.14863
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 GPTQ (TheBloke/Llama-2-7B-Chat-GPTQ)
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Llama 2 7B Chat GPTQ Parameters and Internals

Model Type 
text generation, dialogue optimization
Use Cases 
Areas:
Commercial, Research
Applications:
Assistant-like chat, natural language generation tasks
Primary Use Cases:
Assistant applications, Dialogue management
Limitations:
Not tested exhaustively across languages, Potential for bias and inaccuracy
Considerations:
Developers should ensure thorough safety testing before deployment.
Additional Notes 
This model is static and trained until July 2023. Expected future versions to improve safety based on feedback.
Supported Languages 
en (high)
Training Details 
Data Sources:
A new mix of publicly available online data
Data Volume:
2T tokens
Methodology:
Includes supervised fine-tuning (SFT) and reinforcement learning with human feedback (RLHF)
Context Length:
4000
Hardware Used:
Meta's Research Super Cluster, A100-80GB GPUs, with cumulative 3.3M GPU hours
Model Architecture:
Auto-regressive language model using optimized transformer architecture
Safety Evaluation 
Methodologies:
Internal evaluations
Findings:
Potentially unpredictable outputs, model may produce inaccurate or biased responses
Risk Categories:
Inaccuracy, Bias, Objectionable responses
Ethical Considerations:
Pre-deployment safety testing recommended
Responsible Ai Considerations 
Fairness:
Testing for fairness and bias conducted in English
Transparency:
Reports available for potential risks
Accountability:
Users are responsible for testing tailored to specific applications
Mitigation Strategies:
Recommendations to perform safety tuning tailored to specific applications
Input Output 
Input Format:
Text format with specific tags and tokens such as [INST] and <>
Accepted Modalities:
text
Output Format:
Text
Performance Tips:
Ensure the correct sequence and format of tokens for the best performance.
Release Notes 
Version:
Llama 2
Date:
July 2023
Notes:
Initial release for commercial and research use, focusing on dialogue optimization.
LLM NameLlama 2 7B Chat GPTQ
Repository 🤗https://huggingface.co/TheBloke/Llama-2-7B-Chat-GPTQ 
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 VRAM3.9 GB
Updated2025-09-23
MaintainerTheBloke
Model Typellama
Model Files  3.9 GB
Supported Languagesen
GPTQ QuantizationYes
Quantization Typegptq
Model ArchitectureLlamaForCausalLM
Licensellama2
Context Length4096
Model Max Length4096
Transformers Version4.30.0.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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Rank the Llama 2 7B Chat GPTQ Capabilities

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Instruction Following and Task Automation  
Factuality and Completeness of Knowledge  
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