upload int8 onnx model

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

README.md

@@ -8,6 +8,7 @@ tags:
 - Intel® Neural Compressor
 - neural-compressor
 - PostTrainingDynamic
+- onnx
 datasets:
 - glue
 metrics:
@@ -29,7 +30,9 @@ model-index:
 ---
 # INT8 camembert-base-mrpc
 
-###  Post-training dynamic quantization
+##  Post-training dynamic quantization
+
+### PyTorch
 
 This is an INT8  PyTorch model quantized with [Intel® Neural Compressor](https://github.com/intel/neural-compressor). 
 
@@ -37,14 +40,14 @@ The original fp32 model comes from the fine-tuned model [camembert-base-mrpc](ht
 
 The linear module **roberta.encoder.layer.6.attention.self.query** falls back to fp32 to meet the 1% relative accuracy loss.
 
-### Test result
+#### Test result
 
 |   |INT8|FP32|
 |---|:---:|:---:|
 | **Accuracy (eval-f1)** |0.8843|0.8928|
 | **Model size (MB)**  |180|422|
 
-### Load with Intel® Neural Compressor:
+#### Load with Intel® Neural Compressor:
 
 ```python
 from optimum.intel.neural_compressor import IncQuantizedModelForSequenceClassification
@@ -52,3 +55,24 @@ from optimum.intel.neural_compressor import IncQuantizedModelForSequenceClassifi
 model_id = "Intel/camembert-base-mrpc-int8-dynamic"
 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 [camembert-base-mrpc](https://huggingface.co/Intel/camembert-base-mrpc).
+
+#### Test result
+
+|   |INT8|FP32|
+|---|:---:|:---:|
+| **Accuracy (eval-f1)** |0.8847|0.8928|
+| **Model size (MB)**  |115|423|
+
+
+#### Load ONNX model:
+
+```python
+from optimum.onnxruntime import ORTModelForSequenceClassification
+model = ORTModelForSequenceClassification.from_pretrained('Intel/camembert-base-mrpc-int8-dynamic')
+```

model.onnx

@@ -0,0 +1,3 @@
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+oid sha256:e8f458d3d833494a31eb4d9ab863e1177e632f8e4ae0c7f45888c8f1cedb723f
+size 120091323