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Meta Llama 3 8B Instruct 64K AWQ by heyholetsgo

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Meta Llama 3 8B Instruct 64K AWQ is an open-source language model by heyholetsgo. Features: 8b LLM, VRAM: 5.8GB, Context: 64K, License: other, Quantized, Instruction-Based, HF Score: 64.3, LLM Explorer Score: 0.15, Arc: 59.6, HellaSwag: 78.8, MMLU: 65.1, TruthfulQA: 50.2, WinoGrande: 75, GSM8K: 57.3.

  4-bit   Autotrain compatible   Awq   Conversational   En   Endpoints compatible   Facebook   Instruct   Llama   Llama-3   Meta   Pytorch   Quantized   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/heyholetsgo/Meta-Llama-3-8B-Instruct-64k-awq 

Meta Llama 3 8B Instruct 64K AWQ Benchmarks

ARC: 59.64 vs 96.7 (so35)-38.3%
HellaSwag: 78.84 vs 95.3 (gpt4)-17.3%
MMLU: 65.06 vs 88.3 (so35)-26.3%
TruthfulQA: 50.17 vs 59 (gpt4)-15%
WinoGrande: 74.98 vs 87.5 (gpt4)-14.3%
GSM8K: 57.32 vs 96.4 (so35)-40.5%
LLME Score: 0.14559
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 64K AWQ (heyholetsgo/Meta-Llama-3-8B-Instruct-64k-awq)
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Meta Llama 3 8B Instruct 64K AWQ Parameters and Internals

Model Type 
text-generation
Use Cases 
Areas:
commercial, research
Applications:
natural language generation tasks
Primary Use Cases:
assistant-like chat, custom tuning
Limitations:
Use only in English, Must comply with License and Acceptable Use Policy
Considerations:
Developers may fine-tune for languages beyond English if compliant with License and Acceptable Use Policy.
Supported Languages 
English (Proficient)
Training Details 
Data Sources:
publicly available online data
Data Volume:
15T+ tokens
Methodology:
supervised fine-tuning and reinforcement learning with human feedback
Context Length:
8000
Hardware Used:
Meta's Research SuperCluster, third-party cloud compute
Model Architecture:
optimized transformer architecture
Responsible Ai Considerations 
Mitigation Strategies:
Safety mitigations techniques and responsible LLM-application deployment guidelines.
Input Output 
Input Format:
text
Accepted Modalities:
text
Output Format:
text, code
Release Notes 
Version:
3
Date:
2024-04-18
Notes:
Llama 3 released with improvements in helpfulness and safety.
LLM NameMeta Llama 3 8B Instruct 64K AWQ
Repository 🤗https://huggingface.co/heyholetsgo/Meta-Llama-3-8B-Instruct-64k-awq 
Base Model(s)  ...a Llama 3 8B Instruct 64K PoSE   Azma-AI/Meta-Llama-3-8B-Instruct-64k-PoSE
Model Size8b
Required VRAM5.8 GB
Updated2025-09-23
Maintainerheyholetsgo
Model Typellama
Instruction-BasedYes
Model Files  4.7 GB: 1-of-2   1.1 GB: 2-of-2
Supported Languagesen
AWQ QuantizationYes
Quantization Typeawq
Model ArchitectureLlamaForCausalLM
Licenseother
Context Length65536
Model Max Length65536
Transformers Version4.37.2
Tokenizer ClassPreTrainedTokenizerFast
Vocabulary Size128256
Torch Data Typefloat16

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Note: green Score (e.g. "73.2") means that the model is better than heyholetsgo/Meta-Llama-3-8B-Instruct-64k-awq.

Rank the Meta Llama 3 8B Instruct 64K AWQ 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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