upload int8 onnx model

Signed-off-by: yuwenzho <yuwen.zhou@intel.com>

README.md

@@ -14,7 +14,9 @@ metrics:
 
 # INT8 DistilBERT base uncased finetuned SST-2
 
-###  Post-training static quantization
+## Post-training static quantization
+
+### PyTorch
 
 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). 
 
@@ -23,14 +25,14 @@ The original fp32 model comes from the fine-tuned model [distilbert-base-uncased
 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-accuracy)** |0.9037|0.9106|
 | **Model size (MB)**  |65|255|
 
-### Load with optimum:
+#### Load with optimum:
 
 ```python
 from optimum.intel.neural_compressor.quantization import IncQuantizedModelForSequenceClassification
@@ -38,3 +40,24 @@ int8_model = IncQuantizedModelForSequenceClassification.from_pretrained(
     'Intel/distilbert-base-uncased-finetuned-sst-2-english-int8-static',
 )
 ```
+
+### 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 [distilbert-base-uncased-finetuned-sst-2-english](https://huggingface.co/distilbert-base-uncased-finetuned-sst-2-english).
+
+
+#### Test result
+
+|   |INT8|FP32|
+|---|:---:|:---:|
+| **Accuracy (eval-f1)** |0.9060|0.9106|
+| **Model size (MB)**  |80|256|
+
+#### Load ONNX model:
+
+```python
+from optimum.onnxruntime import ORTModelForSequenceClassification
+model = ORTModelForSequenceClassification.from_pretrained('Intel/distilbert-base-uncased-finetuned-sst-2-english-int8-static')
+```

model.onnx

@@ -0,0 +1,3 @@
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+oid sha256:24cd860d20b786211162fb5c6c41e46ad19dba261c6ae1b64e78af0ebffaff9b
+size 83179400