Meta Llama Meta Llama 3 8B HQQ 1bit Smashed by PrunaAI

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  1bit   Autotrain compatible Base model:finetune:meta-llama... Base model:meta-llama/meta-lla...   Endpoints compatible   Llama   Pruna-ai   Quantized   Region:us

Meta Llama Meta Llama 3 8B HQQ 1bit Smashed Benchmarks

nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Meta Llama Meta Llama 3 8B HQQ 1bit Smashed (PrunaAI/meta-llama-Meta-Llama-3-8B-HQQ-1bit-smashed)

Meta Llama Meta Llama 3 8B HQQ 1bit Smashed Parameters and Internals

Model Type 
compression
Additional Notes 
Efficiency results were obtained after a hardware warmup. Smashed model may benefit specific use-cases under different configurations.
Training Details 
Data Sources:
WikiText
Methodology:
Compression with hqq
Input Output 
Input Format:
Text with tokens
Accepted Modalities:
text
Output Format:
Generated text
Performance Tips:
We recommend testing the efficiency gains directly in your use-cases.
LLM NameMeta Llama Meta Llama 3 8B HQQ 1bit Smashed
Repository ๐Ÿค—https://huggingface.co/PrunaAI/meta-llama-Meta-Llama-3-8B-HQQ-1bit-smashed 
Base Model(s)  Meta Llama 3 8B   meta-llama/Meta-Llama-3-8B
Model Size8b
Required VRAM3.1 GB
Updated2025-02-05
MaintainerPrunaAI
Model Typellama
Model Files  3.1 GB
Quantization Type1bit
Model ArchitectureLlamaForCausalLM
Context Length8192
Model Max Length8192
Transformers Version4.40.0
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 PrunaAI/meta-llama-Meta-Llama-3-8B-HQQ-1bit-smashed.

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Instruction Following and Task Automation  
Factuality and Completeness of Knowledge  
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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241227