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Creating a Whisper pipeline from local checkpoint #2102

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Hello, I first saved the WhisperProcessor before training by using processor.save_pretrained("path/to/local/dir") then after the training is completed I saved the trained model by using trainer.save_model("path/to/local/dir"). Then for using it as a pipeline I used pipeline("automatic-speech-recognition", model="path/to/local/dir")

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@DiwakarBasnet
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