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Llama2 Quantize 4bit by parsawar

 »  All LLMs  »  parsawar  »  Llama2 Quantize 4bit   URL Share it on

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  4-bit   4bit   Autotrain compatible   Bitsandbytes   Conversational   Endpoints compatible   Llama   Quantized   Region:us   Safetensors
Model Card on HF 🤗: https://huggingface.co/parsawar/Llama2_quantize_4bit 

Llama2 Quantize 4bit Benchmarks

LLME Score: 0.1918
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Llama2 Quantize 4bit (parsawar/Llama2_quantize_4bit)

Llama2 Quantize 4bit Parameters and Internals

Model Type 
Text Generation
Use Cases 
Areas:
Research, Commercial Applications
Applications:
Chatbots
Primary Use Cases:
Customer Service, Virtual Assistants
Limitations:
Not suitable for contexts requiring verified factual accuracy
Considerations:
Ensure monitoring of outputs for bias or misinformation
Additional Notes 
Careful tuning required for server deployment to optimize latency.
Supported Languages 
languages (English), proficiency (High)
Training Details 
Data Sources:
Diverse internet text corpus
Data Volume:
Tens of billions of tokens
Methodology:
Standard training followed by quantization
Context Length:
4096
Training Time:
Several weeks
Hardware Used:
NVIDIA GPUs
Model Architecture:
Transformer
Safety Evaluation 
Methodologies:
Adversarial Testing
Findings:
Potential risks in handling specific topics
Risk Categories:
Misinformation, Bias
Ethical Considerations:
Consideration for bias mitigation
Responsible Ai Considerations 
Fairness:
Efforts to minimize bias against specific groups
Transparency:
Quantization details disclosed
Accountability:
Meta AI team accountable for deployments
Mitigation Strategies:
Bias and risk mitigation strategies in place
Input Output 
Input Format:
Text input queries
Accepted Modalities:
Text
Output Format:
Text-based responses
Performance Tips:
Use batching to improve inference speed
Release Notes 
Version:
1.0
Date:
2023-10-21
Notes:
Initial release of the 4-bit quantized model for improved efficiency.
LLM NameLlama2 Quantize 4bit
Repository 🤗https://huggingface.co/parsawar/Llama2_quantize_4bit 
Model Size7b
Required VRAM4.2 GB
Updated2025-02-22
Maintainerparsawar
Model Typellama
Model Files  4.2 GB   4.2 GB
Quantization Type4bit
Model ArchitectureLlamaForCausalLM
Context Length4096
Model Max Length4096
Transformers Version4.41.0
Tokenizer ClassLlamaTokenizer
Vocabulary Size32000
Torch Data Typefloat16

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Rank the Llama2 Quantize 4bit 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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