Fix documentation link (#1443)

Author: TharescdqTuA

docs/source/openvino/export.mdx

@@ -193,7 +193,7 @@ Models larger than 1 billion parameters are exported to the OpenVINO format with
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-Besides weight-only quantization, you can also apply full model quantization including activations by setting `--quant-mode` to preffered precision. This will quantize both weights and activations of Linear, Convolutional and some other layers to selected mode. Please see example below.
+Besides weight-only quantization, you can also apply full model quantization including activations by setting `--quant-mode` to preferred precision. This will quantize both weights and activations of Linear, Convolutional and some other layers to selected mode. Please see example below.
 
 ```bash
 optimum-cli export openvino -m openai/whisper-large-v3-turbo --quant-mode int8 --dataset librispeech --num-samples 32 --smooth-quant-alpha 0.9 ./whisper-large-v3-turbo

docs/source/openvino/inference.mdx

@@ -171,7 +171,7 @@ model = OVModelForSequenceClassification.from_pretrained(model_id, device="gpu",
 
 You can also apply fp16, 8-bit or 4-bit weight compression on the Linear, Convolutional and Embedding layers when loading your model to reduce the memory footprint and inference latency.
 
-For more information on the quantization parameters checkout the [documentation](optimziation#weight-only-quantization).
+For more information on the quantization parameters checkout the [documentation](optimization#weight-only-quantization).
 
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