Update README.md

README.md

@@ -16,8 +16,7 @@ metrics:
 
 ### Post-training static 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 [Intel/MiniLM-L12-H384-uncased-mrpc](https://huggingface.co/Intel/MiniLM-L12-H384-uncased-mrpc).
 
 The calibration dataloader is the train dataloader. The default calibration sampling size 100 isn't divisible exactly by batch size 8, so the real sampling size is 104.
@@ -31,11 +30,11 @@ The linear module **bert.encoder.layer.6.attention.self.key** falls back to fp32
 | **Accuracy (eval-f1)** |0.9039|0.9097|
 | **Model size (MB)**  |33.5|127|
 
-### Load with Intel® Neural Compressor:
+### Load with optimum:
 
 ```python
-from neural_compressor.utils.load_huggingface import OptimizedModel
-int8_model = OptimizedModel.from_pretrained(
+from optimum.intel.neural_compressor.quantization import IncQuantizedModelForSequenceClassification 
+int8_model = IncQuantizedModelForSequenceClassification(
     'Intel/MiniLM-L12-H384-uncased-mrpc-int8-static',
 )
 ```