Creating a Whisper pipeline from local checkpoint #2102
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DiwakarBasnet
DiwakarBasnet
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While creating a whisper huggingface pipeline from local checkpoint, how to save the trainer? Usually we would save model by, |
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Answered by
DiwakarBasnet
May 5, 2024
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Hi Did you find any way for that? |
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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 usingtrainer.save_model("path/to/local/dir")
. Then for using it as a pipeline I usedpipeline("automatic-speech-recognition", model="path/to/local/dir")