upload int8 onnx model

Signed-off-by: yuwenzho <[email protected]>

README.md

@@ -29,7 +29,9 @@ model-index:
 ---
 # INT8 roberta-base-mrpc
 
-###  Post-training static quantization
+##  Post-training static quantization
+
+### PyTorch
 
 This is an INT8  PyTorch model quantized with [Intel® Neural Compressor](https://github.com/intel/neural-compressor). 
 
@@ -37,14 +39,14 @@ The original fp32 model comes from the fine-tuned model [roberta-base-mrpc](http
 
 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.
 
-### Test result
+#### Test result
 
 |   |INT8|FP32|
 |---|:---:|:---:|
 | **Accuracy (eval-f1)** |0.9177|0.9138|
 | **Model size (MB)**  |127|499|
 
-### Load with Intel® Neural Compressor:
+#### Load with Intel® Neural Compressor:
 
 ```python
 from optimum.intel.neural_compressor import IncQuantizedModelForSequenceClassification
@@ -52,3 +54,24 @@ from optimum.intel.neural_compressor import IncQuantizedModelForSequenceClassifi
 model_id = "Intel/roberta-base-mrpc-int8-static"
 int8_model = IncQuantizedModelForSequenceClassification.from_pretrained(model_id)
 ```
+
+### ONNX
+
+This is an INT8 ONNX model quantized with [Intel® Neural Compressor](https://github.com/intel/neural-compressor).
+
+The original fp32 model comes from the fine-tuned model [roberta-base-mrpc](https://huggingface.co/Intel/roberta-base-mrpc).
+
+#### Test result
+
+|   |INT8|FP32|
+|---|:---:|:---:|
+| **Accuracy (eval-f1)** |0.9073|0.9138|
+| **Model size (MB)**  |243|476|
+
+
+#### Load ONNX model:
+
+```python
+from optimum.onnxruntime import ORTModelForSequenceClassification
+model = ORTModelForSequenceClassification.from_pretrained('Intel/roberta-base-mrpc-int8-static')
+```

model.onnx

@@ -0,0 +1,3 @@
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+size 254669454