# INT8 camembert-base-mrpc

##  Post-training dynamic quantization

### PyTorch

This is an INT8  PyTorch 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).

The linear module **roberta.encoder.layer.6.attention.self.query** falls back to fp32 to meet the 1% relative accuracy loss.

#### Test result

|   |INT8|FP32|
|---|:---:|:---:|
| **Accuracy (eval-f1)** |0.8843|0.8928|
| **Model size (MB)**  |180|422|

#### Load with Intel® Neural Compressor:

```python
from optimum.intel.neural_compressor import IncQuantizedModelForSequenceClassification

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)** |0.8819|0.8928|
| **Model size (MB)**  |113|423|


#### Load ONNX model:

```python
from optimum.onnxruntime import ORTModelForSequenceClassification
model = ORTModelForSequenceClassification.from_pretrained('Intel/camembert-base-mrpc-int8-dynamic')
```

{"language": ["en"], "license": "mit", "tags": ["text-classfication", "int8", "Intel\u00ae Neural Compressor", "neural-compressor", "PostTrainingDynamic", "onnx"], "datasets": ["glue"], "metrics": ["f1"], "model-index": [{"name": "camembert-base-mrpc-int8-dynamic", "results": [{"task": {"type": "text-classification", "name": "Text Classification"}, "dataset": {"name": "GLUE MRPC", "type": "glue", "args": "mrpc"}, "metrics": [{"type": "f1", "value": 0.8842832469775476, "name": "F1"}]}]}]}
transformers pytorch onnx camembert text-classification text-classfication int8 Intel® Neural Compressor neural-compressor PostTrainingDynamic en dataset:glue license:mit model-index autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #onnx #camembert #text-classification #text-classfication #int8 #Intel® Neural Compressor #neural-compressor #PostTrainingDynamic #en #dataset-glue #license-mit #model-index #autotrain_compatible #endpoints_compatible #region-us 

INT8 camembert-base-mrpc
========================


Post-training dynamic quantization
----------------------------------


### PyTorch


This is an INT8 PyTorch model quantized with Intel® Neural Compressor.


The original fp32 model comes from the fine-tuned model camembert-base-mrpc.


The linear module URL.6.URL falls back to fp32 to meet the 1% relative accuracy loss.


#### Test result



#### Load with Intel® Neural Compressor:


### ONNX


This is an INT8 ONNX model quantized with Intel® Neural Compressor.


The original fp32 model comes from the fine-tuned model camembert-base-mrpc.


#### Test result



#### Load ONNX model:



### PyTorch


This is an INT8 PyTorch model quantized with Intel® Neural Compressor.


The original fp32 model comes from the fine-tuned model camembert-base-mrpc.


The linear module URL.6.URL falls back to fp32 to meet the 1% relative accuracy loss. #### Test result #### Load with Intel® Neural Compressor: ### ONNX


This is an INT8 ONNX model quantized with Intel® Neural Compressor.


The original fp32 model comes from the fine-tuned model camembert-base-mrpc. #### Test result #### Load ONNX model:
TAGS
#transformers #pytorch #onnx #camembert #text-classification #text-classfication #int8 #Intel® Neural Compressor #neural-compressor #PostTrainingDynamic #en #dataset-glue #license-mit #model-index #autotrain_compatible #endpoints_compatible #region-us 
 ### PyTorch


This is an INT8 PyTorch model quantized with Intel® Neural Compressor.


The original fp32 model comes from the fine-tuned model camembert-base-mrpc.


The linear module URL.6.URL falls back to fp32 to meet the 1% relative accuracy loss. #### Test result #### Load with Intel® Neural Compressor: ### ONNX


This is an INT8 ONNX model quantized with Intel® Neural Compressor.


The original fp32 model comes from the fine-tuned model camembert-base-mrpc. #### Test result #### Load ONNX model:
passage: TAGS
#transformers #pytorch #onnx #camembert #text-classification #text-classfication #int8 #Intel® Neural Compressor #neural-compressor #PostTrainingDynamic #en #dataset-glue #license-mit #model-index #autotrain_compatible #endpoints_compatible #region-us 
### PyTorch


This is an INT8 PyTorch model quantized with Intel® Neural Compressor.


The original fp32 model comes from the fine-tuned model camembert-base-mrpc.


The linear module URL.6.URL falls back to fp32 to meet the 1% relative accuracy loss.#### Test result#### Load with Intel® Neural Compressor:### ONNX


This is an INT8 ONNX model quantized with Intel® Neural Compressor.


The original fp32 model comes from the fine-tuned model camembert-base-mrpc.#### Test result#### Load ONNX model: