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--- |
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license: apache-2.0 |
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tags: |
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- int8 |
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- Intel® Neural Compressor |
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- neural-compressor |
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- PostTrainingDynamic |
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datasets: |
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- cnn_dailymail |
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metrics: |
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- rougeLsum |
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--- |
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# INT8 DistilBart 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 [sshleifer/distilbart-cnn-12-6](https://huggingface.co/sshleifer/distilbart-cnn-12-6). |
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Below linear modules (21/133) are fallbacked to fp32 for less than 1% relative accuracy loss: |
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**'model.decoder.layers.2.fc2'**, **'model.encoder.layers.11.fc2'**, **'model.decoder.layers.1.fc2'**, **'model.decoder.layers.0.fc2'**, **'model.decoder.layers.4.fc1'**, **'model.decoder.layers.3.fc2'**, **'model.encoder.layers.8.fc2'**, **'model.decoder.layers.3.fc1'**, **'model.encoder.layers.11.fc1'**, **'model.encoder.layers.0.fc2'**, **'model.encoder.layers.3.fc1'**, **'model.encoder.layers.10.fc2'**, **'model.decoder.layers.5.fc1'**, **'model.encoder.layers.1.fc2'**, **'model.encoder.layers.3.fc2'**, **'lm_head'**, **'model.encoder.layers.7.fc2'**, **'model.decoder.layers.0.fc1'**, **'model.encoder.layers.4.fc1'**, **'model.encoder.layers.10.fc1'**, **'model.encoder.layers.6.fc1'** |
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### Evaluation result |
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| |INT8|FP32| |
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|---|:---:|:---:| |
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| **Accuracy (eval-rougeLsum)** | 41.4707 | 41.8117 | |
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| **Model size** |722M|1249M| |
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### Load with optimum: |
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```python |
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# transformers <= 4.23.0 |
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from optimum.intel import INCModelForSeq2SeqLM |
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model_id = "Intel/distilbart-cnn-12-6-int8-dynamic" |
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int8_model = INCModelForSeq2SeqLM.from_pretrained(model_id) |
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``` |
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