repo_id = "report-translation-feedback",Ĭheck out this guide to understand how to use the CommitScheduler. Remote repo and local folder are created if they don't already exist. > from huggingface_hub import CommitScheduler # Schedule regular uploads every 10 minutes. The scheduler is designed to remove the hassle of handling background commits while avoiding empty commits. One intended use case is to allow regular backups from a Space to a Dataset repository on the Hub. It watches changes in a folder and creates a commit every 5 minutes if it detected a file change. The CommitScheduler is a new class that can be used to regularly push commits to the Hub. Custom headers/cookies in InferenceClient by in #1507.All calls made with this client will then use these headers/cookies. It is now possible to configure headers and cookies to be sent when initializing the client: InferenceClient(headers=., cookies=.). Fetch inference model for task from API by in #1510.Recommended models are the ones used by default on. In a production-ready setup, we strongly recommend to set the model id/URL manually, as the recommended model is expected to change at any time without prior notice, potentially resulting in different and unexpected results in your workflow. This is useful to quickly prototype and test models. By default, the client will select a model recommended for the selected task and run on the free public Inference API. When using InferenceClient's task methods (text_to_image, text_generation, image_classification.) you don't have to pass a model id. added zero shot image classification by in #1528.Thanks to for your contribution on this task! from huggingface_hub import InferenceClient > client = InferenceClient()
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