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Meta Llama 3 8B by Jccc-l

 »  All LLMs  »  Jccc-l  »  Meta Llama 3 8B   URL Share it on

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

Meta Llama 3 8B Benchmarks

LLME Score: 0.19501
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 (Jccc-l/Meta-Llama-3-8B)

Meta Llama 3 8B Parameters and Internals

Model Type 
Text Generation
Use Cases 
Areas:
Commercial use, Research
Applications:
Assistant-like chat, Natural language generation tasks
Primary Use Cases:
Dialogue use cases, Text generation
Limitations:
Use other than English, Violation of laws, Prohibited uses in Acceptable Use Policy
Considerations:
Fine-tuning for languages beyond English allowed under license compliance
Additional Notes 
Included benchmarks demonstrate performance scaling with model size and modifications to improve model safety.
Supported Languages 
English (Primary)
Training Details 
Data Sources:
Publicly available online data
Data Volume:
15T+ tokens
Methodology:
Supervised fine-tuning (SFT) and reinforcement learning with human feedback (RLHF)
Context Length:
8000
Hardware Used:
Meta's Research SuperCluster and production clusters, third-party cloud compute
Model Architecture:
An auto-regressive language model that uses an optimized transformer architecture
Safety Evaluation 
Methodologies:
Extensive red teaming exercises, Adversarial evaluations, CyberSecEval suite, Child Safety risk assessments
Findings:
Llama 3 significantly less likely to falsely refuse prompts than Llama 2, Drastically reduced residual risks while maintaining helpfulness
Risk Categories:
Child Safety, Cyber Security, CBRNE, General Safety
Ethical Considerations:
Promoting safe, fair, and responsible use; transparency and safety measures implemented
Responsible Ai Considerations 
Fairness:
Reflects a wide range of backgrounds and perspectives
Transparency:
Open consortium involvement, transparency measures in safety evaluation
Accountability:
Developers and Meta are accountable for ensuring proper use
Mitigation Strategies:
Implemented safety best practices; extensive safety evaluations
Input Output 
Input Format:
Text
Accepted Modalities:
Text
Output Format:
Text and code
Performance Tips:
Use pre-trained and instruction tuned variants appropriately for tasks
Release Notes 
Date:
April 18, 2024
Notes:
Initial release of Meta Llama 3 models in 8B and 70B sizes.
LLM NameMeta Llama 3 8B
Repository 🤗https://huggingface.co/Jccc-l/Meta-Llama-3-8B 
Model Size8b
Required VRAM16.1 GB
Updated2025-02-22
MaintainerJccc-l
Model Typellama
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
Licensellama3
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 Jccc-l/Meta-Llama-3-8B.

Rank the Meta Llama 3 8B 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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