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Meta Llama 3 8B Hf by Undi95

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Model Card on HF 🤗: https://huggingface.co/Undi95/Meta-Llama-3-8B-hf 

Meta Llama 3 8B Hf Benchmarks

ARC: 59.22 vs 96.7 (so35)-38.8%
HellaSwag: 82.02 vs 95.3 (gpt4)-13.9%
MMLU: 66.49 vs 88.3 (so35)-24.7%
TruthfulQA: 43.95 vs 59 (gpt4)-25.5%
WinoGrande: 77.11 vs 87.5 (gpt4)-11.9%
GSM8K: 45.34 vs 96.4 (so35)-53%
LLME Score: 0.19803
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 Hf (Undi95/Meta-Llama-3-8B-hf)

Meta Llama 3 8B Hf Parameters and Internals

Model Type 
text generation
Use Cases 
Areas:
Commercial, Research
Applications:
Instruction tuned models for assistant-like chat
Primary Use Cases:
Natural language generation, Multilingual dialogue interactions
Limitations:
Out-of-the-box use only in English, Potential inaccurate or biased responses
Considerations:
Developers should fine-tune based on specific needs.
Additional Notes 
100% carbon emissions offset by Meta’s sustainability program.
Supported Languages 
en (high)
Training Details 
Data Sources:
publicly available online data
Data Volume:
15 trillion tokens
Methodology:
Supervised fine-tuning (SFT) and reinforcement learning with human feedback (RLHF)
Context Length:
8000
Hardware Used:
H100-80GB GPU with a cumulative 7.7M GPU hours
Model Architecture:
Auto-regressive transformer architecture
Safety Evaluation 
Methodologies:
Red teaming exercises, Adversarial evaluations
Risk Categories:
CBRNE, Cyber Security, Child Safety
Ethical Considerations:
Leverages best practices for safety and responsible deployment.
Responsible Ai Considerations 
Fairness:
Inclusive and open approach, aiming to serve diverse user needs and perspectives.
Accountability:
Developers responsible for end-user safety evaluations.
Mitigation Strategies:
Tools like Meta Llama Guard 2 and Code Shield for layering safety measures.
Input Output 
Input Format:
text
Accepted Modalities:
text
Output Format:
text and code
Performance Tips:
Fine-tune with language-specific data where appropriate.
Release Notes 
Version:
Meta Llama 3 (8B, 70B)
Date:
April 18, 2024
Notes:
Initial release of pre-trained and instruction tuned variants.
LLM NameMeta Llama 3 8B Hf
Repository 🤗https://huggingface.co/Undi95/Meta-Llama-3-8B-hf 
Model Size8b
Required VRAM16.1 GB
Updated2025-03-25
MaintainerUndi95
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
Licenseother
Context Length8192
Model Max Length8192
Transformers Version4.40.0.dev0
Tokenizer ClassPreTrainedTokenizerFast
Vocabulary Size128256
Torch Data Typebfloat16

Quantized Models of the Meta Llama 3 8B Hf

Model
Likes
Downloads
VRAM
Meta Llama 3 8B AWQ2595 GB
Meta Llama 3 8B Hf AWQ0135 GB
Meta Llama 3 8B AWQ065 GB
Meta Llama 3 8B AWQ065 GB
Meta Llama 3 8B AWQ095 GB

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Note: green Score (e.g. "73.2") means that the model is better than Undi95/Meta-Llama-3-8B-hf.

Rank the Meta Llama 3 8B Hf Capabilities

🆘 Have you tried this model? Rate its performance. This feedback would greatly assist ML community in identifying the most suitable model for their needs. Your contribution really does make a difference! 🌟

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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