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| import os | |
| import gradio as gr | |
| HF_TOKEN = os.getenv('HF_TOKEN') | |
| hf_writer = gr.HuggingFaceDatasetSaver(HF_TOKEN, "crowdsourced-speech-demo2") | |
| iface = gr.Interface( | |
| lambda x:"Test", | |
| inputs="mic", | |
| outputs="textbox", | |
| title="Crowdsourced Dataset for Speech to Text", | |
| article="This demo uses facebook/wav2vec2-base-960h for a speech-to-text model. Any data that gets flagged is added to the crowdsourced *dataset* found here: [https://huggingface.co/datasets/abidlabs/crowdsourced-speech-demo2](https://huggingface.co/datasets/abidlabs/crowdsourced-speech-demo2). This Space is experimental, and please only flag data that you are comfortable adding to a public dataset!", | |
| allow_flagging="manual", | |
| flagging_callback=hf_writer) | |
| iface.launch() |