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" </td>"
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]
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},
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+ {
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+ "cell_type" : " markdown" ,
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+ "metadata" : {},
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+ "source" : [
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+ " # Install required libraries"
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+ ]
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+ },
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+ {
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+ "cell_type" : " code" ,
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+ "execution_count" : null ,
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+ "metadata" : {},
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+ "outputs" : [],
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+ "source" : [
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+ " #install the required packages\n " ,
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+ " \n " ,
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+ " !pip install -q \" labelbox[data]\"\n " ,
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+ " !pip install -q transformers"
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+ ]
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+ },
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{
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"cell_type" : " markdown" ,
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"metadata" : {},
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"outputs" : [],
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"source" : [
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" # import libraries\n " ,
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- " !pip install -q \" labelbox[data]\"\n " ,
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- " !pip3 install -q transformers\n " ,
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" \n " ,
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" import labelbox as lb\n " ,
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" import transformers\n " ,
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"metadata" : {},
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"outputs" : [],
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"source" : [
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- " # get images from a Labelbox dataset\n " ,
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+ " # get images from a Labelbox dataset, those images needs to be available so you may need a token from your cloud provider \n " ,
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" DATASET_ID = \"\" "
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]
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},
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"metadata" : {},
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"outputs" : [],
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"source" : [
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- " \n " ,
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" export_task = dataset.export_v2()\n " ,
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" \n " ,
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" export_task.wait_till_done()\n " ,
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" new_custom_embedding_id = client.create_embedding(name=\" My new awesome embedding\" , dims=2048).id\n " ,
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" \n " ,
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" #or use an existing embedding from your workspace\n " ,
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- " existing_embedding_id = client.get_embedding_by_name(name=\" ResNet img 2048\" ).id"
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+ " # existing_embedding_id = client.get_embedding_by_name(name=\" ResNet img 2048\" ).id"
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]
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},
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{
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