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Meta Llama 3 8B Instruct by aifeifei798

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Model Card on HF 🤗: https://huggingface.co/aifeifei798/Meta-Llama-3-8B-Instruct 

Meta Llama 3 8B Instruct Benchmarks

LLME Score: 0.19334
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Meta Llama 3 8B Instruct (aifeifei798/Meta-Llama-3-8B-Instruct)

Meta Llama 3 8B Instruct Parameters and Internals

Model Type 
text generation, auto-regressive
Use Cases 
Areas:
Commercial, Research
Applications:
Natural Language Generation
Primary Use Cases:
Assistant-like chat, Tailored natural language processing tasks
Limitations:
Not intended for use in violation of laws or non-English languages without compliance.
Considerations:
Ensure compliance with the Acceptable Use Policy and further fine-tune for language variations.
Additional Notes 
Developers are encouraged to contribute to the community with feedback and improvements using Meta's GitHub resources.
Supported Languages 
English (Advanced proficiency)
Training Details 
Data Sources:
A new mix of publicly available online data, Publicly available instruction datasets, Human-annotated examples
Data Volume:
Public pretraining data with 15 trillion+ tokens and over 10 million human-annotated examples
Methodology:
Pretrained and instruction tuned. Utilizes supervised fine-tuning (SFT) and reinforcement learning with human feedback (RLHF)
Context Length:
8000
Training Time:
Llama 3 used a cumulative 7.7M GPU hours of computation
Hardware Used:
Meta's Research SuperCluster, Third-party cloud compute, Hardware type H100-80GB
Model Architecture:
Optimized transformer architecture with supervised fine-tuning and reinforcement learning with human feedback. Uses Grouped-Query Attention (GQA) for improved inference scalability.
Safety Evaluation 
Methodologies:
Red teaming, Adversarial evaluations, Safety mitigations
Findings:
Model helps in ensuring safety through thoughtful design, but residual risks might remain.
Risk Categories:
Cybersecurity, Child Safety
Ethical Considerations:
Adheres to Responsible AI development principles. Emphasis on open approach, responsible deployment, and essential safety tools.
Responsible Ai Considerations 
Fairness:
Open approach ensures inclusivity with mechanisms to address problematic outputs when identified.
Transparency:
Uses detailed Responsible AI practices and safety toolkits available for the community.
Accountability:
Meta is committed to addressing and mitigating risks with improved public safety measures.
Mitigation Strategies:
Tools like Meta Llama Guard 2 and Code Shield provide safety layers on top of model outputs.
Input Output 
Input Format:
Text
Accepted Modalities:
text
Output Format:
Text and code
Performance Tips:
Optimal for instruction-tuned chat and dynamic text generation contexts.
Release Notes 
Version:
Llama 3
Date:
April 18, 2024
Notes:
First release of the Llama 3 model with substantial advancements in transformer efficiency and safety features.
LLM NameMeta Llama 3 8B Instruct
Repository 🤗https://huggingface.co/aifeifei798/Meta-Llama-3-8B-Instruct 
Model Size8b
Required VRAM16.1 GB
Updated2025-02-22
Maintaineraifeifei798
Model Typellama
Instruction-BasedYes
Model Files  5.0 GB: 1-of-4   5.0 GB: 2-of-4   4.9 GB: 3-of-4   1.2 GB: 4-of-4
Supported Languagesen
Model ArchitectureLlamaForCausalLM
Licenseother
Context Length8192
Model Max Length8192
Transformers Version4.40.0.dev0
Tokenizer ClassPreTrainedTokenizerFast
Vocabulary Size128256
Torch Data Typebfloat16

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Note: green Score (e.g. "73.2") means that the model is better than aifeifei798/Meta-Llama-3-8B-Instruct.

Rank the Meta Llama 3 8B Instruct 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 v20241227
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