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Meta Llama 3 70B Instruct GPTQ 8B by cortecs

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Meta Llama 3 70B Instruct GPTQ 8B is an open-source language model by cortecs. Features: 70b LLM, VRAM: 74.4GB, Context: 8K, License: other, Quantized, Instruction-Based, LLM Explorer Score: 0.13.

  8-bit   8bit   Autotrain compatible   Conversational   Dataset:wikitext   Endpoints compatible   Gptq   Instruct   Llama   Quantized   Region:us   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/cortecs/Meta-Llama-3-70B-Instruct-GPTQ-8b 

Meta Llama 3 70B Instruct GPTQ 8B Benchmarks

LLME Score: 0.13417
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 70B Instruct GPTQ 8B (cortecs/Meta-Llama-3-70B-Instruct-GPTQ-8b)
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Meta Llama 3 70B Instruct GPTQ 8B Parameters and Internals

Model Type 
quantized, GPTQ, instruction-tuned
Additional Notes 
This model is a quantized version using 8bit precision with specific configurations for performance.
Supported Languages 
languages_supported_and_proficiency_levels ()
LLM NameMeta Llama 3 70B Instruct GPTQ 8B
Repository 🤗https://huggingface.co/cortecs/Meta-Llama-3-70B-Instruct-GPTQ-8b 
Base Model(s)  Llama3v1   aryansiddiqui/llama3v1
Model Size70b
Required VRAM74.4 GB
Updated2025-11-30
Maintainercortecs
Model Typellama
Instruction-BasedYes
Model Files  10.0 GB: 1-of-8   9.8 GB: 2-of-8   9.9 GB: 3-of-8   9.9 GB: 4-of-8   10.0 GB: 5-of-8   9.9 GB: 6-of-8   9.9 GB: 7-of-8   5.0 GB: 8-of-8
GPTQ QuantizationYes
Quantization Typegptq|8bit
Model ArchitectureLlamaForCausalLM
Licenseother
Context Length8192
Model Max Length8192
Transformers Version4.40.1
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 cortecs/Meta-Llama-3-70B-Instruct-GPTQ-8b.

Rank the Meta Llama 3 70B Instruct GPTQ 8B 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  
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