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Facebook Opt 125M HQQ 1bit Smashed by PrunaAI

 »  All LLMs  »  PrunaAI  »  Facebook Opt 125M HQQ 1bit Smashed   URL Share it on

  16   
  1bit   Autotrain compatible   Endpoints compatible   Opt   Pruna-ai   Quantized   Region:us
Model Card on HF 🤗: https://huggingface.co/PrunaAI/facebook-opt-125m-HQQ-1bit-smashed 

Facebook Opt 125M HQQ 1bit Smashed Benchmarks

LLME Score: 0.18486
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Facebook Opt 125M HQQ 1bit Smashed (PrunaAI/facebook-opt-125m-HQQ-1bit-smashed)

Facebook Opt 125M HQQ 1bit Smashed Parameters and Internals

Additional Notes 
Metrics include memory_disk, memory_inference, inference_latency, inference_throughput, inference_CO2_emissions, inference_energy_consumption. Calibration data if needed, was WikiText.
Training Details 
Data Sources:
WikiText
Methodology:
hqq compression
Hardware Used:
NVIDIA A100-PCIE-40GB
Input Output 
Performance Tips:
We recommend testing efficiency gains directly in use-cases.
LLM NameFacebook Opt 125M HQQ 1bit Smashed
Repository 🤗https://huggingface.co/PrunaAI/facebook-opt-125m-HQQ-1bit-smashed 
Model Size125m
Required VRAM0.1 GB
Updated2025-01-17
MaintainerPrunaAI
Model Typeopt
Model Files  0.1 GB
Quantization Type1bit
Model ArchitectureOPTForCausalLM
Context Length2048
Model Max Length2048
Transformers Version4.37.1
Vocabulary Size50272
Torch Data Typefloat16
Activation Functionrelu

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Note: green Score (e.g. "73.2") means that the model is better than PrunaAI/facebook-opt-125m-HQQ-1bit-smashed.

Rank the Facebook Opt 125M HQQ 1bit Smashed Capabilities

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Release v20241227
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