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Meta Llama 3.1 8B Instruct by NousResearch

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  Arxiv:2204.05149   Autotrain compatible   Conversational   De   En   Endpoints compatible   Es   Facebook   Fr   Hi   Instruct   It   Llama   Llama-3   Meta   Pt   Pytorch   Region:us   Safetensors   Sharded   Tensorflow   Th
Model Card on HF 🤗: https://huggingface.co/NousResearch/Meta-Llama-3.1-8B-Instruct 

Meta Llama 3.1 8B Instruct Benchmarks

MMLU Pro: 26.82
GPQA: 5.48
MUSR: 11.56
BBH: 30.03
IFEval: 46.56 vs 88 (so35)-47.1%
MATH Lvl 5: 4.38
LLME Score: 0.33089
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Meta Llama 3.1 8B Instruct (NousResearch/Meta-Llama-3.1-8B-Instruct)

Meta Llama 3.1 8B Instruct Parameters and Internals

Model Type 
Text Generation
Use Cases 
Areas:
Commercial applications, Research
Applications:
Multilingual dialogue use cases, Instruction tuned text applications
Primary Use Cases:
Assistant-like chat, Natural language generation tasks
Limitations:
Use in non-supported languages not recommended without fine-tuning, Adherence to license and Acceptable Use Policy necessary
Considerations:
Compliance with laws and regulations
Additional Notes 
Static model with offline dataset; future versions will integrate community feedback for enhanced safety
Supported Languages 
en (English), de (German), fr (French), it (Italian), pt (Portuguese), hi (Hindi), es (Spanish), th (Thai)
Training Details 
Data Sources:
A new mix of publicly available online data.
Data Volume:
~15T tokens of data
Methodology:
Supervised fine-tuning (SFT) and reinforcement learning with human feedback (RLHF)
Context Length:
128000
Hardware Used:
Meta's custom built GPU cluster
Model Architecture:
Optimized transformer architecture
Safety Evaluation 
Methodologies:
Adversarial testing, Responsible AI guidelines, Red teaming
Findings:
Maintained net zero greenhouse gas emissions
Risk Categories:
Misinformation, Bias, Prohibited uses, Critical risk areas
Ethical Considerations:
Following Responsible Use Guide
Responsible Ai Considerations 
Fairness:
Focus on equitable and impartial treatment across different user backgrounds
Transparency:
Openness about model capabilities and limitations, safety concerns
Accountability:
Meta and developers are responsible for the use of the model
Mitigation Strategies:
Incorporation of red-teaming and community feedback for improvements
Input Output 
Input Format:
Multilingual Text
Accepted Modalities:
text
Output Format:
Multilingual Text and code
Performance Tips:
Utilize supervised fine-tuning to align with human preferences
Release Notes 
Version:
3.1
Date:
July 23, 2024
Notes:
Release of instruction tuned versions, focus on multilingual dialogue use cases
LLM NameMeta Llama 3.1 8B Instruct
Repository 🤗https://huggingface.co/NousResearch/Meta-Llama-3.1-8B-Instruct 
Model Size8b
Required VRAM16.1 GB
Updated2025-02-22
MaintainerNousResearch
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 de fr it pt hi es th
Model ArchitectureLlamaForCausalLM
Licensemeta
Context Length131072
Model Max Length131072
Transformers Version4.42.3
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 NousResearch/Meta-Llama-3.1-8B-Instruct.

Rank the Meta Llama 3.1 8B Instruct 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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