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Meta Llama 3 8B by NousResearch

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Meta Llama 3 8B is an open-source language model by NousResearch. Features: 8b LLM, VRAM: 16.1GB, Context: 8K, License: other, LLM Explorer Score: 0.28.

  Autotrain compatible   En   Endpoints compatible   Facebook   Llama   Llama-3   Meta   Pytorch   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/NousResearch/Meta-Llama-3-8B 

Meta Llama 3 8B Benchmarks

MMLU Pro: 22.8
GPQA: 5.7
MUSR: 11.25
BBH: 30.67
IFEval: 53.62 vs 88 (so35)-39.1%
MATH Lvl 5: 6.19
LLME Score: 0.27608
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 (NousResearch/Meta-Llama-3-8B)
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Meta Llama 3 8B 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
Repository 🤗https://huggingface.co/NousResearch/Meta-Llama-3-8B 
Model Size8b
Required VRAM16.1 GB
Updated2025-09-23
MaintainerNousResearch
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

Model
Likes
Downloads
VRAM
...mes 2 Pro Llama 3 8B Bpw6 EXL2056 GB
Hermes 2 Pro Llama 3 8B Marlin175 GB
...ta Llama 3 8B HQQ 4bit Smashed065 GB
...ta Llama 3 8B HQQ 2bit Smashed054 GB

Best Alternatives to Meta Llama 3 8B

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Context / RAM
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...otron 8B UltraLong 4M Instruct4192K / 32.1 GB1531120
...a 3.1 8B UltraLong 4M Instruct4192K / 32.1 GB17624
UltraLong Thinking4192K / 16.1 GB13
...a 3.1 8B UltraLong 2M Instruct2096K / 32.1 GB8759
...otron 8B UltraLong 2M Instruct2096K / 32.1 GB10515
...otron 8B UltraLong 1M Instruct1048K / 32.1 GB156156
...a 3.1 8B UltraLong 1M Instruct1048K / 32.1 GB138729
...xis Bookwriter Llama3.1 8B Sft1048K / 16.1 GB64
Zero Llama 3.1 8B Beta61048K / 16.1 GB21
...dger Nu Llama 3.1 8B UltraLong1048K / 16.2 GB03

Rank the Meta Llama 3 8B 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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