update the titles of tutorial to a normal one

Signed-off-by: binliu <[email protected]>

Author: binliunls

hugging_face/hugging_face_pipeline_for_monai.ipynb

@@ -29,7 +29,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## Setup Environment \n",
+    "## Setup environment \n",
     "MONAI installation has the optional dependencies needed for this tutorial. Therefore installing MONAI with necessary optional dependiencies is recommanded for this turtorial."
    ]
   },
@@ -46,7 +46,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## Setup Imports"
+    "## Setup imports"
    ]
   },
   {
@@ -137,7 +137,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## Setup Data Directory\n",
+    "## Setup data directory\n",
     "\n",
     "You can specify a directory with the `MONAI_DATA_DIRECTORY` environment variable. This allows you to save results and reuse downloads. If not specified a temporary directory will be used."
    ]
@@ -159,7 +159,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## Download Dataset\n",
+    "## Download dataset\n",
     "\n",
     "Downloads and extracts the dataset. The dataset comes from http://medicaldecathlon.com/."
    ]
@@ -183,7 +183,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## Get Inference Dataset"
+    "## Get inference dataset"
    ]
   },
   {
@@ -200,7 +200,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## Define the Model Configuration\n",
+    "## Define the model configuration\n",
     "\n",
     "A PretrainedConfig in Hugging Face's Transformers library is a class that holds the configuration parameters for a model. This configuration includes information such as model architecture details, hyperparameters, and other settings that define how the model behaves. The PretrainedConfig is used to initialize a model with a specific configuration or to load a model's configuration from a pre-trained checkpoint.\n",
     "\n",
@@ -241,7 +241,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## Define a Hugging Face Pretrained Model\n",
+    "## Define a hugging face pretrained model\n",
     "\n",
     "A PreTrainedModel in Hugging Face's Transformers library is a base class for all model classes. It provides common functionalities for loading, saving, and configuring models. This class is designed to work seamlessly with PretrainedConfig, allowing users to load pre-trained models from the Hugging Face Hub or from local files. The PreTrainedModel class ensures consistency and ease of use across different model architectures.\n",
     "\n",
@@ -277,7 +277,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## Build a Hugging Face Pipeline\n",
+    "## Build a hugging face pipeline\n",
     "\n",
     "A Hugging Face pipeline is a high-level API that simplifies the process of using pre-trained models for various tasks such as text classification, image classification, object detection, and more. It abstracts the complexity of loading models and tokenizers, making it easy to perform inference with just a few lines of code. The pipeline handles the preprocessing of inputs, passing data through the model, and post-processing of outputs.\n",
     "\n",
@@ -450,7 +450,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## Run Pipeline\n",
+    "## Run pipeline\n",
     "\n",
     "In this section, we will instantiate the pipeline and run inference with it."
    ]