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Meta Llama 3.3 70B Instruct AWQ INT4 by ibnzterrell

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Model Card on HF 🤗: https://huggingface.co/ibnzterrell/Meta-Llama-3.3-70B-Instruct-AWQ-INT4 

Meta Llama 3.3 70B Instruct AWQ INT4 Benchmarks

LLME Score: 0.2678
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Meta Llama 3.3 70B Instruct AWQ INT4 (ibnzterrell/Meta-Llama-3.3-70B-Instruct-AWQ-INT4)
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Meta Llama 3.3 70B Instruct AWQ INT4 Parameters and Internals

LLM NameMeta Llama 3.3 70B Instruct AWQ INT4
Repository 🤗https://huggingface.co/ibnzterrell/Meta-Llama-3.3-70B-Instruct-AWQ-INT4 
Base Model(s)  meta-llama/Llama-3.3-70B-Instruct   meta-llama/Llama-3.3-70B-Instruct
Model Size70b
Required VRAM39.9 GB
Updated2025-09-23
Maintaineribnzterrell
Model Typellama
Instruction-BasedYes
Model Files  5.0 GB: 1-of-9   4.9 GB: 2-of-9   4.9 GB: 3-of-9   4.9 GB: 4-of-9   4.9 GB: 5-of-9   4.9 GB: 6-of-9   4.9 GB: 7-of-9   3.4 GB: 8-of-9   2.1 GB: 9-of-9
Supported Languagesen fr it pt hi es th de
AWQ QuantizationYes
Quantization Typeawq
Model ArchitectureLlamaForCausalLM
Licensemeta
Context Length131072
Model Max Length131072
Transformers Version4.47.0
Tokenizer ClassPreTrainedTokenizerFast
Padding Token<|finetune_right_pad_id|>
Vocabulary Size128256
Torch Data Typefloat16

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...0B Instruct Gradient 1048K AWQ1024K / 39.9 GB131
...70B Instruct Gradient 262K AWQ256K / 39.9 GB60
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... Llama 3 70B Instruct AWQ GEMM8K / 39.9 GB60
Note: green Score (e.g. "73.2") means that the model is better than ibnzterrell/Meta-Llama-3.3-70B-Instruct-AWQ-INT4.

Rank the Meta Llama 3.3 70B Instruct AWQ INT4 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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Release v20241124
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