Unable to run whisper small finetune after training

Beginners
1

I have fine tuned whisper small for Urdu using this huggingface post. The original is for Hindi, so basically I just changed “hi” to “ur” and it worked as there is similar amount of data for Urdu available on Mozilla Common Voice.
Now I wanna run the model locally using this code chunk (again from the above guide):

from transformers import pipeline
import gradio as gr

pipe = pipeline(model="sanchit-gandhi/whisper-small-hi")  # change to "your-username/the-name-you-picked"

def transcribe(audio):
    text = pipe(audio)["text"]
    return text

iface = gr.Interface(
    fn=transcribe, 
    inputs=gr.Audio(source="microphone", type="filepath"), 
    outputs="text",
    title="Whisper Small Hindi",
    description="Realtime demo for Hindi speech recognition using a fine-tuned Whisper small model.",
)

iface.launch()

However I am unable to understand how to specifiy the path to my local checkpoint-5000 folder or another folder where I saved the pre-trained model using trainer.save_model. There are many posts online on how to load pre-trained (like this one). I always get error when using these methods feature_extractor not present, or tokenizer or something else (these files are not present neither in checkpoint-5000 nor in whisper-small-ur where I manually save using trainer.save_model). Any help will be appreciated.

2

Somebody asked it previously and got it solved.

The following line should follow before trainer.train() to save the configuration
processor.save_pretrained(training_args.output_dir)
One wonders why the original post has not been updated with the missing info?!

3

If anyone doesn’t raise an issue on the Hugging Face github, the author won’t notice it and it won’t get fixed…:sob: