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Llama 3 70B Instruct AWQ by mattmalcher

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  4-bit   Autotrain compatible   Awq   Conversational   Endpoints compatible   Instruct   Llama   Quantized   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/mattmalcher/Llama-3-70B-Instruct-awq 

Llama 3 70B Instruct AWQ Benchmarks

LLME Score: 0.16639
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Llama 3 70B Instruct AWQ (mattmalcher/Llama-3-70B-Instruct-awq)
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Llama 3 70B Instruct AWQ Parameters and Internals

Additional Notes 
User wanted to convert Meta model weights to an AWQ-quantized model.
LLM NameLlama 3 70B Instruct AWQ
Repository 🤗https://huggingface.co/mattmalcher/Llama-3-70B-Instruct-awq 
Base Model(s)  Llama 3 70B Instruct 32K   maywell/Llama-3-70B-Instruct-32k
Model Size70b
Required VRAM39.9 GB
Updated2025-07-30
Maintainermattmalcher
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
AWQ QuantizationYes
Quantization Typeawq
Model ArchitectureLlamaForCausalLM
Licensellama3
Context Length8192
Model Max Length8192
Transformers Version4.41.2
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 mattmalcher/Llama-3-70B-Instruct-awq.

Rank the Llama 3 70B Instruct AWQ Capabilities

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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241124
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