![]() Similarly, the number of people added to one group is 512 which is increased from 256. So avoid the limitations of the original one and create groups separately according to your contacts. Pipeline(task=“document-question-answering”) Pipeline(task=“automatic-speech-recognition”)Īnswer a question about the image, given an image and a questionĪnswer a question about the document, given a document and a question Predict the bounding boxes and classes of objects in an image Generate a summary of a sequence of text or documentĪssign a label to each individual pixel of an image (supports semantic, panoptic, and instance segmentation) TaskĪssign a label to a given sequence of text For a complete list of available tasks, check out the pipeline API reference.Unlike the official app, TM Whatsapp allows you to create groups as many as you want. Start by creating an instance of pipeline() and specifying a task you want to use it for. ![]() In this guide, you’ll use the pipeline() for sentiment analysis as an example:Ĭopied > result = speech_recognizer(dataset)įor larger datasets where the inputs are big (like in speech or vision), you’ll want to pass a generator instead of a list to load all the inputs in memory. Use another model and tokenizer in the pipeline Take a look at the pipeline API reference for more information. The pipeline() can accommodate any model from the Hub, making it easy to adapt the pipeline() for other use-cases. For example, if you’d like a model capable of handling French text, use the tags on the Hub to filter for an appropriate model.
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