README.md

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.neural_compressor.quantization import IncQuantizedModelForSeq2SeqLM
int8_model = IncQuantizedModelForSeq2SeqLM.from_pretrained(
    'Intel/t5-small-xsum-int8-dynamic',
)