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Llama 3.3 70B Instruct AWQ by casperhansen

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  4-bit   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   Pt   Quantized   Region:us   Safetensors   Sharded   Tensorflow   Th
Model Card on HF 🤗: https://huggingface.co/casperhansen/llama-3.3-70b-instruct-awq 

Llama 3.3 70B Instruct AWQ Benchmarks

LLME Score: 0.39565
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Llama 3.3 70B Instruct AWQ (casperhansen/llama-3.3-70b-instruct-awq)

Llama 3.3 70B Instruct AWQ Parameters and Internals

LLM NameLlama 3.3 70B Instruct AWQ
Repository 🤗https://huggingface.co/casperhansen/llama-3.3-70b-instruct-awq 
Base Model(s)  meta-llama/Llama-3.1-70B   meta-llama/Llama-3.1-70B
Model Size70b
Required VRAM39.9 GB
Updated2024-12-21
Maintainercasperhansen
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
Licensellama3.3
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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Rank the Llama 3.3 70B Instruct 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  
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Multi-Language Support and Translation  

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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241217
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