#deepneurones = pipeline("text2text-generation", model="google/flan-t5-small")
#deepneurones = pipeline("automatic-speech-recognition")# la liste des pipelines de huggingface est disponible ici :https://huggingface.co/docs/transformers/quicktour. pipeline() telecharge dans un cache local le modele deeplearning
from transformers import pipeline  # le framework de huggingface
deepneurones= pipeline("automatic-speech-recognition", model="facebook/wav2vec2-base-960h") # il faut choisir un modele

#from pyannote.audio import Pipeline
#,use_auth_token="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")
#deepneuronesdiarizatin = Pipeline.from_pretrained("pyannote/speaker-diarization",use_auth_token="test")


class AudioAnalyserAnglais:

    @classmethod
    def stt(cls, file_content):
        return deepneurones(file_content)