bofenghuang

/

whisper-small-cv11-french

like 3

Hello,

I would like to use your model (the aim is to transcribe an audio record from a meeting to text).
Here is my code snippet (yes, I know, it would me cleaner to create functions, call them, but for the moment it is just to test if the script works):
[code]

Imports

from pathlib import Path
import streamlit as st
import torch

from tempfile import NamedTemporaryFile
from datasets import load_dataset
from transformers import pipeline

Initialize environment

device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
pipe = pipeline("automatic-speech-recognition", model="bofenghuang/whisper-small-cv11-french", device=device)
pipe.model.config.forced_decoder_ids = pipe.tokenizer.get_decoder_prompt_ids(language="fr", task="transcribe")

Display

st.title("Télécharger un enregistrement de réunion pour obtenir sa transcription en texte")
col1, col2 = st.columns(2)
audio_source=st.sidebar.file_uploader(label="Choisir votre fichier", type=["wav","m4a","mp3","wma"])

Variables

suffix = ""
predicted_sentence = ""

Processing

if audio_source is not None:
col1.toast("Début du traitement")
waveform = audio_source.getvalue()
col1.toast("Lancement du pipe")
predicted_sentence = pipe(waveform, max_new_tokens=225)
col2.write("Transcription :")
col2.write(predicted_sentence)
col2.download_button(label="Télécharger la transcription", data=predicted_sentence, file_name="transcript.txt",mime="text/plain")
[/code]

It results in an error :
[code]
ValueError: You have passed more than 3000 mel input features (> 30 seconds) which automatically enables long-form generation which requires the generation config to have no_timestamps_token_id correctly. Make sure to initialize the generation config with the correct attributes that are needed such as no_timestamps_token_id. For more details on how to generate the approtiate config, refer to https://github.com/huggingface/transformers/issues/21878#issuecomment-1451902363or make sure to pass no more than 3000 mel input features.
Traceback:
File "/home/ild/miniconda3/envs/transcript/lib/python3.10/site-packages/streamlit/runtime/scriptrunner/script_runner.py", line 542, in _run_script
exec(code, module.dict)
File "/home/ild/whisperFR.py", line 34, in
predicted_sentence = pipe(waveform, max_new_tokens=225)
File "/home/ild/.local/lib/python3.10/site-packages/transformers/pipelines/automatic_speech_recognition.py", line 292, in call
return super().call(inputs, **kwargs)
File "/home/ild/.local/lib/python3.10/site-packages/transformers/pipelines/base.py", line 1154, in call
return next(
File "/home/ild/.local/lib/python3.10/site-packages/transformers/pipelines/pt_utils.py", line 124, in next
item = next(self.iterator)
File "/home/ild/.local/lib/python3.10/site-packages/transformers/pipelines/pt_utils.py", line 266, in next
processed = self.infer(next(self.iterator), **self.params)
File "/home/ild/.local/lib/python3.10/site-packages/transformers/pipelines/base.py", line 1068, in forward
model_outputs = self._forward(model_inputs, **forward_params)
File "/home/ild/.local/lib/python3.10/site-packages/transformers/pipelines/automatic_speech_recognition.py", line 507, in _forward
tokens = self.model.generate(
File "/home/ild/.local/lib/python3.10/site-packages/transformers/models/whisper/generation_whisper.py", line 502, in generate
self._set_return_timestamps(
File "/home/ild/.local/lib/python3.10/site-packages/transformers/models/whisper/generation_whisper.py", line 969, in _set_return_timestamps
raise ValueError(
[/code]

I don't know if the problem is due to copy/pasting a script intended to train and fine-tune the model, just an argument I should pass somewhere or if I need to find another model (which would be small enough to be used with a 4GB GPU)?

Thank you