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Meta Llama 3.3 70B Instruct AWQ INT4 by ibnzterrell

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  4-bit   Autoawq   Autotrain compatible   Awq Base model:meta-llama/llama-3.... Base model:quantized:meta-llam...   Conversational   De   En   Endpoints compatible   Es   Fr   Hi   Instruct   It   Llama   Llama-3.3   Meta   Pt   Quantized   Region:us   Safetensors   Sharded   Tensorflow   Th
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: 0.36838
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)

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
Updated2024-12-22
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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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  
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Release v20241217
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