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Meta Llama 3 8B GPTQ Instruct by boadisamson

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  4-bit   4bit   Autotrain compatible   Endpoints compatible   Gptq   Instruct   Llama   Quantized   Region:us
Model Card on HF 🤗: https://huggingface.co/boadisamson/Meta-Llama-3-8B-GPTQ-Instruct 

Meta Llama 3 8B GPTQ Instruct 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: 0.1961
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 GPTQ Instruct (boadisamson/Meta-Llama-3-8B-GPTQ-Instruct)

Meta Llama 3 8B GPTQ Instruct Parameters and Internals

LLM NameMeta Llama 3 8B GPTQ Instruct
Repository 🤗https://huggingface.co/boadisamson/Meta-Llama-3-8B-GPTQ-Instruct 
Base Model(s)  Meta Llama 3 13B Instruct   andrijdavid/Meta-Llama-3-13B-Instruct
Model Size8b
Required VRAM5.7 GB
Updated2025-02-15
Maintainerboadisamson
Model Typellama
Instruction-BasedYes
Model Files  5.7 GB
GPTQ QuantizationYes
Quantization Typegptq|4bit
Model ArchitectureLlamaForCausalLM
Context Length8192
Model Max Length8192
Transformers Version4.39.3
Vocabulary Size128256
Torch Data Typefloat16

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

Rank the Meta Llama 3 8B GPTQ Instruct Capabilities

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Instruction Following and Task Automation  
Factuality and Completeness of Knowledge  
Censorship and Alignment  
Data Analysis and Insight Generation  
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Release v20241227
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