1) fine-tuning on as few as 15 harmful examples or 100 benign examples can remove core safeguards from GPT-4, 2) GPT-4 Assistants divulge the function call schema and can be made to execute arbitrary function calls, and 3) knowledge retrieval can be hijacked by injecting instructions into ...
$schema:https://azuremlsdk2.blob.core.windows.net/preview/0.0.1/autoMLJob.schema.jsontype:automlexperiment_name:dpv2-cli-automl-image-classification-experimentdescription:Amulti-classImageclassificationjobusingfridgeitemsdatasetcompute:azureml:gpu-clustertask:image_classificationlog_verbosity:debugprimary_metr...
程序集: Microsoft.ML.ImageAnalytics.dll 包: Microsoft.ML.ImageAnalytics v3.0.1 返回SchemaShape 由转换器生成的架构。用于管道中的架构传播和验证。 C# 复制 public override Microsoft.ML.SchemaShape GetOutputSchema (Microsoft.ML.SchemaShape inputSchema); 参数 inputSchema SchemaShape 返回 SchemaShape ...
Image Assembly: Microsoft.ML.ImageAnalytics.dll Package: Microsoft.ML.ImageAnalytics v3.0.1 Returns the SchemaShape of the schema which will be produced by the transformer. Used for schema propagation and verification in a pipeline. C# Copy public override Microsoft.ML.SchemaShape Ge...
1) Genie - a foundation model trained from internet videos and with the ability to generate a variety of action-controllable 2D worlds given an image prompt; Genie has 11B parameters and consists of a spatiotemporal video tokenizer, an autoregressive dynamic model, and a scalable latent action ...
} private static void PrintColumns(IDataView transformedData) { Console.WriteLine("{0, -25} {1, -25} {2, -25}", "Features", "Image", "Pixels"); using (var cursor = transformedData.GetRowCursor(transformedData .Schema)) { // Note that it is best to get the getters and values *be...
Image featurization Time Series (preview) Support for ONNX and TensorFlow model integration (preview) Other Model understanding and explainability User-defined custom transformations Schema operations Support for dataset manipulation and cross-validation ...
idv.Schema[predictedBoundingBoxColumnName], idv.Schema[scoreColumnName] ); 命名实体识别和问答 自然语言处理(Natural Language Processing)是软件中最常见的ML需求之一。NLP 最重要的两个进步领域是问答 (QA) 和命名实体识别 (NER)。在http://ML.NET3.0中,这两种场景通过在http://ML.NET2.0中引入的现有TorchS...
Then, just write the following code and run it so you see the training IDataView schema: Copy display(h1("Code for loading the data into IDataViews: training dataset and test dataset"));MLContextmlContext=newMLContext(seed:0);stringTrainDataPath="./taxi-fare-train.csv";stringTestDataPath="...
and then consume or query it for analysis. If you can apply a schema on top of the dataset, then it’s straightforward to query because you can load the data into a database or impose a virtual table schema for querying. But in the case of unstructured data, metadata di...