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--- |
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license: mit |
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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 [facebook/bart-large-cnn](https://huggingface.co/facebook/bart-large-cnn). |
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Below linear modules (40/193) are fallbacked to fp32 for less than 1% relative accuracy loss: |
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**'model.decoder.layers.10.fc1'**, **'model.decoder.layers.0.fc2'**, |
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**'model.decoder.layers.4.fc2'**, **'model.decoder.layers.1.fc2'**, |
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**'model.decoder.layers.6.fc2'**, **'model.decoder.layers.2.fc2'**, |
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**'model.decoder.layers.3.fc2'**, **'model.encoder.layers.11.fc2'**, |
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**'model.decoder.layers.9.fc1'**, **'model.decoder.layers.5.fc2'**, |
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**'model.decoder.layers.7.fc1'**, **'model.decoder.layers.8.fc1'**, |
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**'model.encoder.layers.0.fc2'**, **'model.decoder.layers.11.fc1'**, |
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**'model.encoder.layers.8.fc2'**, **'model.encoder.layers.11.fc1'**, |
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**'model.decoder.layers.8.fc2'**, **'model.decoder.layers.2.fc1'**, |
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**'model.decoder.layers.11.self_attn.v_proj'**, **'model.encoder.layers.9.fc1'**, |
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**'model.decoder.layers.9.fc2'**, **'model.decoder.layers.7.fc2'**, |
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**'model.decoder.layers.6.fc1'**, **'model.decoder.layers.0.fc1'**, |
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**'model.decoder.layers.1.self_attn.v_proj'**, **'model.encoder.layers.3.fc1'**, |
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**'model.encoder.layers.2.fc2'**, **'model.encoder.layers.7.fc2'**, |
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**'model.decoder.layers.3.fc1'**, **'model.encoder.layers.1.fc2'**, |
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**'model.encoder.layers.10.fc2'**, **'model.encoder.layers.8.fc1'**, |
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**'lm_head'**, **'model.decoder.layers.6.self_attn.v_proj'**, |
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**'model.decoder.layers.11.self_attn.out_proj'**, **'model.decoder.layers.11.encoder_attn.v_proj'**, |
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**'model.encoder.layers.10.fc1'**, **'model.encoder.layers.6.fc1'**, |
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**'model.decoder.layers.4.fc1'**, **'model.decoder.layers.1.fc1'** |
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### Evaluation result |
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| |INT8|FP32| |
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|---|:---:|:---:| |
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| **Accuracy (eval-rougeLsum)** | 41.2224 | 41.5274 | |
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| **Model size** |625M|1669M| |
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### Load with optimum: |
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```python |
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from optimum.intel import INCModelForSeq2SeqLM |
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model_id = "Intel/bart-large-cnn-int8-dynamic" |
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int8_model = INCModelForSeq2SeqLM.from_pretrained(model_id) |
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``` |
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