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# INT8 T5 large finetuned on CNN DailyMail
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### Post-training dynamic quantization
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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).
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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).
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### Evaluation result
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| |INT8|FP32|
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| **Accuracy (eval-rougeLsum)** | 29.6346 |29.7451|
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| **Model size** |879M|3021M|
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### Load with optimum:
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```python
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from optimum.intel.neural_compressor.quantization import IncQuantizedModelForSeq2SeqLM
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int8_model = IncQuantizedModelForSeq2SeqLM.from_pretrained(
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---
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# INT8 T5 large finetuned on CNN DailyMail
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+
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### Post-training dynamic quantization
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+
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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).
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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).
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### Evaluation result
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| |INT8|FP32|
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|---|:---:|:---:|
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| **Accuracy (eval-rougeLsum)** | 29.6346 |29.7451|
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| **Model size** |879M|3021M|
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### Load with optimum:
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```python
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from optimum.intel.neural_compressor.quantization import IncQuantizedModelForSeq2SeqLM
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int8_model = IncQuantizedModelForSeq2SeqLM.from_pretrained(
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