readme: ---
  license: mit
  tags:
  - int8
  - Intel® Neural Compressor
  - neural-compressor
  - PostTrainingDynamic
  datasets: 
  - cnn_dailymail
  metrics:
  - rougeLsum
  ---
  
  # INT8 DistilBart 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 [facebook/bart-large-cnn](https://huggingface.co/facebook/bart-large-cnn).
  
  Below linear modules (40/193) are fallbacked to fp32 for less than 1% relative accuracy loss:
  
  **'model.decoder.layers.10.fc1'**, **'model.decoder.layers.0.fc2'**, 
  **'model.decoder.layers.4.fc2'**, **'model.decoder.layers.1.fc2'**, 
  **'model.decoder.layers.6.fc2'**, **'model.decoder.layers.2.fc2'**, 
  **'model.decoder.layers.3.fc2'**, **'model.encoder.layers.11.fc2'**, 
  **'model.decoder.layers.9.fc1'**, **'model.decoder.layers.5.fc2'**, 
  **'model.decoder.layers.7.fc1'**, **'model.decoder.layers.8.fc1'**, 
  **'model.encoder.layers.0.fc2'**, **'model.decoder.layers.11.fc1'**, 
  **'model.encoder.layers.8.fc2'**, **'model.encoder.layers.11.fc1'**, 
  **'model.decoder.layers.8.fc2'**, **'model.decoder.layers.2.fc1'**, 
  **'model.decoder.layers.11.self_attn.v_proj'**, **'model.encoder.layers.9.fc1'**, 
  **'model.decoder.layers.9.fc2'**, **'model.decoder.layers.7.fc2'**, 
  **'model.decoder.layers.6.fc1'**, **'model.decoder.layers.0.fc1'**, 
  **'model.decoder.layers.1.self_attn.v_proj'**, **'model.encoder.layers.3.fc1'**, 
  **'model.encoder.layers.2.fc2'**, **'model.encoder.layers.7.fc2'**, 
  **'model.decoder.layers.3.fc1'**, **'model.encoder.layers.1.fc2'**, 
  **'model.encoder.layers.10.fc2'**, **'model.encoder.layers.8.fc1'**, 
  **'lm_head'**, **'model.decoder.layers.6.self_attn.v_proj'**, 
  **'model.decoder.layers.11.self_attn.out_proj'**, **'model.decoder.layers.11.encoder_attn.v_proj'**, 
  **'model.encoder.layers.10.fc1'**, **'model.encoder.layers.6.fc1'**, 
  **'model.decoder.layers.4.fc1'**, **'model.decoder.layers.1.fc1'**
  
  ### Evaluation result
  
  |   |INT8|FP32|
  |---|:---:|:---:|
  | **Accuracy (eval-rougeLsum)** | 41.2224 | 41.5274 |
  | **Model size**  |625M|1669M|
  
  ### Load with optimum:
  
  ```python
  from optimum.intel.neural_compressor.quantization import IncQuantizedModelForSeq2SeqLM
  int8_model = IncQuantizedModelForSeq2SeqLM.from_pretrained(
      'Intel/bart-large-cnn-int8-dynamic',
  )
  ```