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metadata
license: apache-2.0
tags:
  - int8
  - Intel® Neural Compressor
  - neural-compressor
  - PostTrainingDynamic
datasets:
  - mnli
metrics:
  - accuracy

INT8 T5 small finetuned on XSum

Post-training dynamic quantization

This is an INT8 PyTorch model quantized with huggingface/optimum-intel through the usage of Intel® Neural Compressor.

The original fp32 model comes from the fine-tuned model adasnew/t5-small-xsum.

The linear modules lm.head, fall back to fp32 for less than 1% relative accuracy loss.

Evaluation result

INT8 FP32
Accuracy (eval-rouge1) 29.9008 29.9592
Model size 154M 242M

Load with optimum:

from optimum.intel import INCModelForSeq2SeqLM

model_id = "Intel/t5-small-xsum-int8-dynamic-inc"
int8_model = INCModelForSeq2SeqLM.from_pretrained(model_id)