Update README.md

README.md

@@ -3,7 +3,7 @@ license: apache-2.0
 tags:
 - int8
 - Intel® Neural Compressor
-- PostTrainingStatic
+- PostTrainingDynamic
 datasets: 
 - mnli
 metrics:
@@ -14,7 +14,7 @@ metrics:
 
 ### Post-training dynamic quantization
 
-This is an INT8  PyTorch model quantized with [Intel® Neural Compressor](https://github.com/intel/neural-compressor). 
+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 [adasnew/t5-small-xsum](https://huggingface.co/adasnew/t5-small-xsum).
 
@@ -29,11 +29,11 @@ The linear modules **lm.head**, fall back to fp32 for less than 1% relative accu
 | **Accuracy (eval-rouge1)** | 29.9008 |29.9592|
 | **Model size**  |154M|242M|
 
-### Load with Intel® Neural Compressor:
+### Load with optimum:
 
 ```python
-from neural_compressor.utils.load_huggingface import OptimizedModel
-int8_model = OptimizedModel.from_pretrained(
-    'Intel/roberta-base-squad2-int8-static',
+from optimum.intel.neural_compressor.quantization import IncQuantizedModelForSeq2SeqLM
+int8_model = IncQuantizedModelForSeq2SeqLM.from_pretrained(
+    'Intel/t5-small-xsum-int8-dynamic',
 )
 ```