Open allandclive opened 7 months ago
Hi Allan, the easiest way to do this for me is to do something like that (I haven't tested the code but it should work). It's basically converting the audio column to something that datasets
understand
from datasets import load_dataset, Audio
dataset = load_dataset("Sunbird/salt-studio-lug")
dataset = dataset.map(lambda s: {"audio": s[0], "sampling_rate": s[1]}, input_columns=["audio", "sample_rate")
dataset = dataset.cast_column("audio", Audio())
dataset.push_to_hub(THE DATASET NAME YOU WANT)
Then you can use the newly created dataset as indicated in the README
Let me give it a try
Error
TypeError: Couldn't cast array of type list<item: float> to struct<bytes: binary, path: string>
is there is any way to fine tune this model with https://huggingface.co/datasets/mozilla-foundation/common_voice_16_1 this one dataset have any one have experience of doing it ?
https://huggingface.co/datasets/Sunbird/salt-studio-lug
how do I load & fine tune using this dataset