| license: mit | |
| tags: | |
| - int8 | |
| - Intel® Neural Compressor | |
| - neural-compressor | |
| - PostTrainingDynamic | |
| datasets: | |
| - cnn_dailymail | |
| metrics: | |
| - rougeLsum | |
| # INT8 T5 large finetuned on CNN DailyMail | |
| ### Post-training dynamic quantization | |
| This is an INT8 PyTorch model quantized with [huggingface/optimum-intel](https://github.com/huggingface/optimum-intel) through the usage of [Intel® Neural Compressor](https://github.com/intel/neural-compressor). | |
| The original fp32 model comes from the fine-tuned model [sysresearch101/t5-large-finetuned-xsum-cnn](https://huggingface.co/sysresearch101/t5-large-finetuned-xsum-cnn). | |
| ### Evaluation result | |
| | |INT8|FP32| | |
| |---|:---:|:---:| | |
| | **Accuracy (eval-rougeLsum)** | 29.6346 |29.7451| | |
| | **Model size** |879M|3021M| | |
| ### Load with optimum: | |
| ```python | |
| from optimum.intel import INCModelForSeq2SeqLM | |
| model_id = "Intel/t5-large-finetuned-xsum-cnn-int8-dynamic" | |
| int8_model = INCModelForSeq2SeqLM.from_pretrained(model_id) | |
| ``` | |