Update README.md

README.md

@@ -1,3 +1,34 @@
 ---
 license: apache-2.0
+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 [sysresearch101/t5-large-finetuned-xsum-cnn](https://huggingface.co/sysresearch101/t5-large-finetuned-xsum-cnn).
+
+Below linear modules are fallbacked to fp32 for less than 1% relative accuracy loss:
+
+**'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'**
+
+### Evaluation result
+|   |INT8|FP32|
+|---|:---:|:---:|
+| **Accuracy (eval-rougeLsum)** | 41.4707 | 41.8117 |
+| **Model size**  |722M|1249M|
+### Load with optimum:
+```python
+from optimum.intel.neural_compressor.quantization import IncQuantizedModelForSeq2SeqLM
+int8_model = IncQuantizedModelForSeq2SeqLM.from_pretrained(
+    'Intel/distilbart-cnn-12-6-int8-dynamic',
+)
+```