Update README.md

README.md

@@ -1,3 +1,39 @@
 ---
 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 [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:
+
+
+### 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/bart-large-cnn-int8-dynamic',
+)
+```