Fix documentation (#369)

* fix class * Update optimization.mdx
huggingface · Sep 6, 2022 · 815a762 · 815a762
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diff --git a/docs/source/onnxruntime/optimization.mdx b/docs/source/onnxruntime/optimization.mdx
@@ -22,10 +22,10 @@ The `ORTOptimizer` class is used to optimize your ONNX model. The class can be i
 1. Using an already initialized `ORTModelForXXX` class.
 
 ```python
->>> from optimum.onnxruntime import ORTOptimizer, ORTModelForTextClassification
+>>> from optimum.onnxruntime import ORTOptimizer, ORTModelForSequenceClassification
 
 # Loading ONNX Model from the Hub
->>> model = ORTModelForTextClassification.from_pretrained("optimum/distilbert-base-uncased-finetuned-sst-2-english")
+>>> model = ORTModelForSequenceClassification.from_pretrained("optimum/distilbert-base-uncased-finetuned-sst-2-english")
 
 # Create an optimizer from an ORTModelForXXX
 >>> optimizer = ORTOptimizer.from_pretrained(model)
@@ -112,4 +112,4 @@ Below you will find an easy end-to-end example on how to optimize a Seq2Seq mode
 ## ORTOptimizer
 
 [[autodoc]] onnxruntime.optimization.ORTOptimizer
- - all
+ - all
diff --git a/docs/source/onnxruntime/quantization.mdx b/docs/source/onnxruntime/quantization.mdx
@@ -21,10 +21,10 @@ The `ORTQuantizer` class is used to quantize your ONNX model. The class can be i
 1. Using an already initialized `ORTModelForXXX` class.
 
 ```python
->>> from optimum.onnxruntime import ORTQuantizer, ORTModelForTextClassification
+>>> from optimum.onnxruntime import ORTQuantizer, ORTModelForSequenceClassification
 
 # Loading ONNX Model from the Hub
->>> ort_model = ORTModelForTextClassification.from_pretrained("optimum/distilbert-base-uncased-finetuned-sst-2-english")
+>>> ort_model = ORTModelForSequenceClassification.from_pretrained("optimum/distilbert-base-uncased-finetuned-sst-2-english")
 
 # Create a quantizer from a ORTModelForXXX
 >>> quantizer = ORTQuantizer.from_pretrained(ort_model)
@@ -169,4 +169,4 @@ The `ORTQuantizer` currently doesn't support multi-file models, like `ORTModelFo
 ## ORTQuantizer
 
 [[autodoc]] onnxruntime.quantization.ORTQuantizer
- - all
+ - all