Merge branch 'roll-back-torch-verision' into dependabot/pip/openai-whisper-20240930

2024-10-11 10:39:52 +02:00
parent b07f593fab 3851311ffc
commit fec46aa563
10 changed files with 109 additions and 339 deletions
@@ -1,18 +1,14 @@
 name: Publish Python 🐍 distribution 📦 to PyPI and TestPyPI
 on:
  pull_request_target:
    branches:
      - develop
    types:
      - closed
    paths: 
      - scraibe/**
      - pyproject.toml
  push:
    tags:
      - 'v*.*.*'
    branches: 
      - "develop"
    paths: 
      - "scraibe/**"
      - "pyproject.toml"
  workflow_dispatch:
    inputs:
@@ -27,13 +23,7 @@ on:
 jobs: 
  Build-and-publish-to-Test-PyPI:
-    if: |
+    if: github.event_name != 'workflow_dispatch' || github.event.inputs.test == 'true'
      (github.event_name == 'workflow_dispatch' &&
       github.event.inputs.test == 'true') ||
      (github.event_name == 'pull_request_target' &&
       github.event.pull_request.merged &&
       contains(github.event.pull_request.labels.*.name, 'release')) ||
      (github.event_name == 'push' && startsWith(github.ref, 'refs/tags/'))
    runs-on: ubuntu-latest
    steps: 
      - uses: actions/checkout@v4
@@ -72,28 +62,16 @@ jobs:
    needs: Test-PyPi-install
    runs-on: ubuntu-latest
    if: |
-      always() &&
+        always() &&
-      (( needs.Build-and-publish-to-Test-PyPI.result  != 'failure' &&
+        (( needs.Build-and-publish-to-Test-PyPI.result  != 'failure' &&
-        needs.Test-PyPi-install.result != 'failure' ) &&
+          needs.Test-PyPi-install.result != 'failure' ) ||
-      ((github.event_name == 'workflow_dispatch' &&
+        ((github.event_name == 'workflow_dispatch' &&
-      github.event.inputs.publish_to_pypi == 'true') ||
+        github.event.inputs.publish_to_pypi == 'true')))
      (github.event_name == 'pull_request_target' &&
      github.event.pull_request.merged &&
      contains(github.event.pull_request.labels.*.name, 'release')) ||
      (github.event_name == 'push' && startsWith(github.ref, 'refs/tags/'))))
    steps: 
      - name: Checkout Repository Tags
        uses: actions/checkout@v4
        if: github.ref == 'refs/heads/main'
        with:
          fetch-depth: '0'
          branch: 'main'
      - name: Checkout Repository (Develop)
        uses: actions/checkout@v4
        if: github.ref == 'refs/heads/develop'
        with:
          fetch-depth: '0'
          branch: 'develop'
      - name: Set up Poetry 📦
        uses: JRubics/poetry-publish@v1.16
        with:
@@ -1,256 +0,0 @@
 channels:
  - pytorch
  - defaults
 dependencies:
  - _libgcc_mutex=0.1=main
  - _openmp_mutex=5.1=1_gnu
  - blas=1.0=mkl
  - brotlipy=0.7.0=py39h27cfd23_1003
  - bzip2=1.0.8=h7b6447c_0
  - ca-certificates=2023.05.30=h06a4308_0
  - certifi=2023.5.7=py39h06a4308_0
  - cffi=1.15.1=py39h5eee18b_3
  - cryptography=39.0.1=py39h9ce1e76_2
  - cudatoolkit=11.3.1=h2bc3f7f_2
  - ffmpeg=4.2.2=h20bf706_0
  - flit-core=3.8.0=py39h06a4308_0
  - freetype=2.12.1=h4a9f257_0
  - giflib=5.2.1=h5eee18b_3
  - gmp=6.2.1=h295c915_3
  - gnutls=3.6.15=he1e5248_0
  - idna=3.4=py39h06a4308_0
  - intel-openmp=2021.4.0=h06a4308_3561
  - jpeg=9e=h5eee18b_1
  - lame=3.100=h7b6447c_0
  - lcms2=2.12=h3be6417_0
  - ld_impl_linux-64=2.38=h1181459_1
  - lerc=3.0=h295c915_0
  - libdeflate=1.17=h5eee18b_0
  - libffi=3.4.2=h6a678d5_6
  - libgcc-ng=11.2.0=h1234567_1
  - libgomp=11.2.0=h1234567_1
  - libidn2=2.3.2=h7f8727e_0
  - libopus=1.3.1=h7b6447c_0
  - libpng=1.6.39=h5eee18b_0
  - libstdcxx-ng=11.2.0=h1234567_1
  - libtasn1=4.16.0=h27cfd23_0
  - libtiff=4.5.0=h6a678d5_2
  - libunistring=0.9.10=h27cfd23_0
  - libuv=1.44.2=h5eee18b_0
  - libvpx=1.7.0=h439df22_0
  - libwebp=1.2.4=h11a3e52_1
  - libwebp-base=1.2.4=h5eee18b_1
  - lz4-c=1.9.4=h6a678d5_0
  - mkl=2021.4.0=h06a4308_640
  - mkl-service=2.4.0=py39h7f8727e_0
  - mkl_fft=1.3.1=py39hd3c417c_0
  - mkl_random=1.2.2=py39h51133e4_0
  - ncurses=6.4=h6a678d5_0
  - nettle=3.7.3=hbbd107a_1
  - numpy=1.23.5=py39h14f4228_0
  - numpy-base=1.23.5=py39h31eccc5_0
  - openh264=2.1.1=h4ff587b_0
  - openssl=3.0.9=h7f8727e_0
  - pillow=9.4.0=py39h6a678d5_0
  - pip=23.0.1=py39h06a4308_0
  - pycparser=2.21=pyhd3eb1b0_0
  - pyopenssl=23.0.0=py39h06a4308_0
  - pysocks=1.7.1=py39h06a4308_0
  - python=3.9.16=h955ad1f_3
  - pytorch=1.11.0=py3.9_cuda11.3_cudnn8.2.0_0
  - pytorch-mutex=1.0=cuda
  - readline=8.2=h5eee18b_0
  - requests=2.28.1=py39h06a4308_1
  - setuptools=65.6.3=py39h06a4308_0
  - six=1.16.0=pyhd3eb1b0_1
  - sqlite=3.41.2=h5eee18b_0
  - tk=8.6.12=h1ccaba5_0
  - torchaudio=0.11.0=py39_cu113
  - torchvision=0.12.0=py39_cu113
  - tzdata=2023c=h04d1e81_0
  - wheel=0.38.4=py39h06a4308_0
  - x264=1!157.20191217=h7b6447c_0
  - xz=5.4.2=h5eee18b_0
  - zlib=1.2.13=h5eee18b_0
  - zstd=1.5.4=hc292b87_0
  - pip:
      - absl-py==1.3.0
      - aiofiles==23.1.0
      - aiohttp==3.8.3
      - aiosignal==1.3.1
      - alembic==1.9.1
      - altair==5.0.1
      - annotated-types==0.5.0
      - ansi2html==1.8.0
      - antlr4-python3-runtime==4.9.3
      - anyio==3.7.1
      - appdirs==1.4.4
      - asteroid-filterbanks==0.4.0
      - async-timeout==4.0.2
      - attrs==22.2.0
      - audioread==3.0.0
      - autopage==0.5.1
      - backports-cached-property==1.0.2
      - cachetools==5.2.0
      - charset-normalizer==2.1.1
      - click==8.1.3
      - cliff==4.1.0
      - cmaes==0.9.0
      - cmake==3.26.4
      - cmd2==2.4.2
      - colorama==0.4.6
      - colorlog==6.7.0
      - commonmark==0.9.1
      - contourpy==1.0.6
      - cycler==0.11.0
      - dash==2.12.1
      - dash-core-components==2.0.0
      - dash-html-components==2.0.0
      - dash-table==5.0.0
      - decorator==4.4.2
      - docopt==0.6.2
      - einops==0.3.2
      - exceptiongroup==1.1.1
      - fastapi==0.100.0
      - ffmpeg-python==0.2.0
      - ffmpy==0.3.0
      - filelock==3.8.0
      - flask==2.2.5
      - fonttools==4.38.0
      - frozenlist==1.3.3
      - fsspec==2022.11.0
      - future==0.18.2
      - google-auth==2.15.0
      - google-auth-oauthlib==0.4.6
      - gradio==3.36.1
      - gradio-client==0.2.7
      - greenlet==2.0.1
      - grpcio==1.51.1
      - h11==0.14.0
      - hmmlearn==0.2.8
      - httpcore==0.17.3
      - httpx==0.24.1
      - huggingface-hub==0.16.4
      - humanize==4.7.0
      - hyperpyyaml==1.1.0
      - imageio==2.23.0
      - imageio-ffmpeg==0.4.7
      - importlib-metadata==4.13.0
      - importlib-resources==5.12.0
      - iniconfig==2.0.0
      - itsdangerous==2.1.2
      - jinja2==3.1.2
      - joblib==1.2.0
      - jsonschema==4.18.0
      - jsonschema-specifications==2023.6.1
      - julius==0.2.7
      - kiwisolver==1.4.4
      - librosa==0.9.2
      - linkify-it-py==2.0.2
      - lit==16.0.5.post0
      - llvmlite==0.39.1
      - mako==1.2.4
      - markdown==3.4.1
      - markdown-it-py==2.2.0
      - markupsafe==2.1.1
      - matplotlib==3.7.1
      - mdit-py-plugins==0.3.3
      - mdurl==0.1.2
      - more-itertools==9.0.0
      - moviepy==1.0.3
      - mpmath==1.2.1
      - multidict==6.0.4
      - nest-asyncio==1.5.7
      - networkx==2.8.8
      - numba==0.56.4
      - oauthlib==3.2.2
      - omegaconf==2.3.0
      - openai-whisper==20230314
      - optuna==3.0.5
      - orjson==3.9.2
      - packaging==21.3
      - pandas==1.5.2
      - pbr==5.11.0
      - plotly==5.15.0
      - pluggy==1.0.0
      - pooch==1.6.0
      - prettytable==3.5.0
      - primepy==1.3
      - proglog==0.1.10
      - protobuf==3.20.1
      - pyannote-audio==2.1.1
      - pyannote-core==4.5
      - pyannote-database==4.1.3
      - pyannote-metrics==3.2.1
      - pyannote-pipeline==2.3
      - pyasn1==0.4.8
      - pyasn1-modules==0.2.8
      - pydantic==2.0.2
      - pydantic-core==2.1.2
      - pydeprecate==0.3.2
      - pydub==0.25.1
      - pygments==2.13.0
      - pyparsing==3.0.9
      - pyperclip==1.8.2
      - pytest==7.3.1
      - python-dateutil==2.8.2
      - python-multipart==0.0.6
      - pytorch-lightning==1.6.5
      - pytorch-metric-learning==1.6.3
      - pytz==2022.7
      - pyyaml==6.0
      - qtfaststart==1.8
      - referencing==0.29.1
      - regex==2022.10.31
      - requests-oauthlib==1.3.1
      - resampy==0.4.2
      - retrying==1.3.4
      - rich==12.6.0
      - rpds-py==0.8.10
      - rsa==4.9
      - ruamel-yaml==0.17.21
      - ruamel-yaml-clib==0.2.7
      - ruff==0.0.272
      - scikit-learn==1.2.0
      - scipy==1.8.1
      - semantic-version==2.10.0
      - semver==2.13.0
      - sentencepiece==0.1.97
      - setuptools-rust==1.5.2
      - shellingham==1.5.0
      - simplejson==3.18.0
      - singledispatchmethod==1.0
      - sniffio==1.3.0
      - sortedcontainers==2.4.0
      - soundfile==0.10.3.post1
      - speechbrain==0.5.14
      - sqlalchemy==1.4.45
      - starlette==0.27.0
      - stevedore==4.1.1
      - sympy==1.11.1
      - tabulate==0.9.0
      - tenacity==8.2.2
      - tensorboard==2.11.0
      - tensorboard-data-server==0.6.1
      - tensorboard-plugin-wit==1.8.1
      - threadpoolctl==3.1.0
      - tiktoken==0.3.1
      - tokenizers==0.13.2
      - tomli==2.0.1
      - toolz==0.12.0
      - torch-audiomentations==0.11.0
      - torch-pitch-shift==1.2.2
      - torchmetrics==0.11.0
      - tqdm==4.64.1
      - transformers==4.24.0
      - triton==2.0.0
      - typer==0.7.0
      - typing-extensions==4.7.1
      - uc-micro-py==1.0.2
      - urllib3==1.26.12
      - uvicorn==0.22.0
      - wcwidth==0.2.5
      - websockets==11.0.3
      - werkzeug==2.2.2
      - yarl==1.8.2
      - zipp==3.11.0
@@ -31,12 +31,12 @@ exclude =[
        ]
 [tool.poetry.dependencies]
 python = "^3.9"
-tqdm = "^4.66.4"
+tqdm = "^4.66.5"
 numpy = "^1.26.4"
 openai-whisper = ">=20231117,<20240931"
-whisperx = "^3.1.3"
+faster-whisper = "^1.0.3"
-"pyannote.audio" = "^3.1.1"
+"pyannote.audio" = "^3.3.1"
-torch = "^2.3.0"
+torch = "^2.1.2"
 [tool.poetry.group.dev.dependencies]
 pytest = "^8.1.1"
@@ -57,7 +57,7 @@ format-jinja = """
 [tool.poetry.group.docs.dependencies]
 sphinx = "^7.3.7"
-sphinx-rtd-theme = "^2.0.0"
+sphinx-rtd-theme = ">=2,<4"
 markdown-it-py = {version = "~3.0.0", extras = ["plugins"]}
 myst-parser = "^3.0.1"
 mdit-py-plugins = "^0.4.1"
@@ -1,14 +1,14 @@
-tqdm>=4.65.0
+tqdm>=4.66.5
 numpy>=1.26.4
 openai-whisper==20231117
-whisperx~=3.1.3
+faster-whisper~=1.0.3
-pyannote.audio~=3.1.1
+pyannote.audio~=3.3.1
 pyannote.core~=5.0.0
 pyannote.database~=5.0.1 
 pyannote.metrics~=3.2.1
 pyannote.pipeline~=3.0.1
-torch>=2.0.0
+torchaudio>=2.1.2
@@ -74,7 +74,7 @@ class Scraibe:
            whisper_model (Union[bool, str, whisper], optional): 
                                Path to whisper model or whisper model itself.
            whisper_type (str):
-                                Type of whisper model to load. "whisper" or "whisperx".
+                                Type of whisper model to load. "whisper" or "faster-whisper".
            diarisation_model (Union[bool, str, DiarisationType], optional): 
                                Path to pyannote diarization model or model itself.
            **kwargs: Additional keyword arguments for whisper
@@ -36,8 +36,8 @@ def cli():
                        help="List of audio files to transcribe.")
    parser.add_argument("--whisper-type", type=str, default="whisper",
-                        choices=["whisper", "whisperx"],
+                        choices=["whisper", "faster-whisper"],
-                        help="Type of Whisper model to use ('whisper' or 'whisperx').")
+                        help="Type of Whisper model to use ('whisper' or 'faster-whisper').")
    parser.add_argument("--whisper-model-name", default="medium",
                        help="Name of the Whisper model to use.")
@@ -79,6 +79,8 @@ def cli():
                        choices=sorted(
                            LANGUAGES.keys()) + sorted([k.title() for k in TO_LANGUAGE_CODE.keys()]),
                        help="Language spoken in the audio. Specify None to perform language detection.")
    parser.add_argument("--num-speakers", type=int, default=2,
                        help="Number of speakers in the audio.")
    args = parser.parse_args()
@@ -117,8 +119,13 @@ def cli():
                else:
                    task = "transcribe"
-                out = model.autotranscribe(audio, task=task, language=arg_dict.pop(
+                out = model.autotranscribe(
-                    "language"), verbose=arg_dict.pop("verbose_output"))
+                        audio, 
                        task=task, 
                        language=arg_dict.pop("language"), 
                        verbose=arg_dict.pop("verbose_output"),
                        num_speakers=arg_dict.pop("num_speakers")
                        )
                basename = audio.split("/")[-1].split(".")[0]
                print(f'Saving {basename}.{out_format} to {out_folder}')
                out.save(os.path.join(
@@ -1,6 +1,5 @@
 import os
 import yaml
 from pyannote.audio.core.model import CACHE_DIR as PYANNOTE_CACHE_DIR
 from argparse import Action
 from ast import literal_eval
@@ -8,15 +7,16 @@ CACHE_DIR = os.getenv(
    "AUTOT_CACHE",
    os.path.expanduser("~/.cache/torch/models"),
 )
-
+os.getenv(
-if CACHE_DIR != PYANNOTE_CACHE_DIR:
+    "PYANNOTE_CACHE",
-    os.environ["PYANNOTE_CACHE"] = os.path.join(CACHE_DIR, "pyannote")
+    os.path.join(CACHE_DIR, "pyannote"),
 )
 WHISPER_DEFAULT_PATH = os.path.join(CACHE_DIR, "whisper")
 PYANNOTE_DEFAULT_PATH = os.path.join(CACHE_DIR, "pyannote")
 PYANNOTE_DEFAULT_CONFIG = os.path.join(PYANNOTE_DEFAULT_PATH, "config.yaml") \
    if os.path.exists(os.path.join(PYANNOTE_DEFAULT_PATH, "config.yaml")) \
-    else ('jaikinator/scraibe', 'pyannote/speaker-diarization-3.1')
+    else ('Jaikinator/ScrAIbe', 'pyannote/speaker-diarization-3.1')
 def config_diarization_yaml(file_path: str, path_to_segmentation: str = None) -> None:
@@ -26,8 +26,9 @@ Usage:
 from whisper import Whisper
 from whisper import load_model as whisper_load_model
-from whisperx.asr import WhisperModel
+from whisper.tokenizer import TO_LANGUAGE_CODE
-from whisperx import load_model as whisperx_load_model
+from faster_whisper import WhisperModel as FasterWhisperModel
 from faster_whisper.tokenizer import _LANGUAGE_CODES as FASTER_WHISPER_LANGUAGE_CODES
 from typing import TypeVar, Union, Optional
 from torch import Tensor, device
 from torch.cuda import is_available as cuda_is_available
@@ -145,7 +146,7 @@ class Transcriber:
                        - 'large-v3'
                        - 'large'
            whisper_type (str):
-                                Type of whisper model to load. "whisper" or "whisperx".
+                                Type of whisper model to load. "whisper" or "faster-whisper".
            download_root (str, optional): Path to download the model.
                                            Defaults to WHISPER_DEFAULT_PATH.
            device (Optional[Union[str, torch.device]], optional): 
@@ -272,7 +273,7 @@ class WhisperTranscriber(Transcriber):
        return f"WhisperTranscriber(model_name={self.model_name}, model={self.model})"
-class WhisperXTranscriber(Transcriber):
+class FasterWhisperTranscriber(Transcriber):
    def __init__(self, model: whisper, model_name: str) -> None:
        super().__init__(model, model_name)
@@ -294,10 +295,10 @@ class WhisperXTranscriber(Transcriber):
        if isinstance(audio, Tensor):
            audio = audio.cpu().numpy()
-        result = self.model.transcribe(audio, *args, **kwargs)
+        result, _ = self.model.transcribe(audio, *args, **kwargs)
        text = ""
-        for seg in result['segments']:
+        for seg in result:
-            text += seg['text']
+            text += seg.text
        return text
    @classmethod
@@ -306,7 +307,7 @@ class WhisperXTranscriber(Transcriber):
                   download_root: str = WHISPER_DEFAULT_PATH,
                   device: Optional[Union[str, device]] = None,
                   *args, **kwargs
-                   ) -> 'WhisperXTranscriber':
+                   ) -> 'FasterWhisperModel':
        """
        Load whisper model.
@@ -347,8 +348,8 @@ class WhisperXTranscriber(Transcriber):
            warnings.warn(f'Compute type {compute_type} not compatible with '
                          f'device {device}! Changing compute type to int8.')
            compute_type = 'int8'
-        _model = whisperx_load_model(model, download_root=download_root,
+        _model = FasterWhisperModel(model, download_root=download_root,
-                                     device=device, compute_type=compute_type)
+                                    device=device, compute_type=compute_type)
        return cls(_model, model_name=model)
@@ -361,7 +362,7 @@ class WhisperXTranscriber(Transcriber):
            dict: Keyword arguments for whisper model.
        """
        # _possible_kwargs = WhisperModel.transcribe.__code__.co_varnames
-        _possible_kwargs = signature(WhisperModel.transcribe).parameters.keys()
+        _possible_kwargs = signature(FasterWhisperModel.transcribe).parameters.keys()
        whisper_kwargs = {k: v for k,
                          v in kwargs.items() if k in _possible_kwargs}
@@ -370,12 +371,42 @@ class WhisperXTranscriber(Transcriber):
            whisper_kwargs["task"] = task
        if (language := kwargs.get("language")):
            language = FasterWhisperTranscriber.convert_to_language_code(language)
            whisper_kwargs["language"] = language
        return whisper_kwargs
    @staticmethod
    def convert_to_language_code(lang : str) -> str:
        """
        Load whisper model.
        Args:
            lang (str): language as code or language name
        Returns:
            language (str) code of language 
        """
        # If the input is already in FASTER_WHISPER_LANGUAGE_CODES, return it directly
        if lang in FASTER_WHISPER_LANGUAGE_CODES:
            return lang
        # Normalize the input to lowercase
        lang = lang.lower()
        # Check if the language name is in the TO_LANGUAGE_CODE mapping
        if lang in TO_LANGUAGE_CODE:
            return TO_LANGUAGE_CODE[lang]
        # If the language is not recognized, raise a ValueError with the available options
        available_codes = ', '.join(FASTER_WHISPER_LANGUAGE_CODES)
        raise ValueError(f"Language '{lang}' is not a valid language code or name. "
                        f"Available language codes are: {available_codes}.")
    def __repr__(self) -> str:
-        return f"WhisperXTranscriber(model_name={self.model_name}, model={self.model})"
+        return f"FasterWhisperTranscriber(model_name={self.model_name}, model={self.model})"
 def load_transcriber(model: str = "medium",
@@ -384,7 +415,7 @@ def load_transcriber(model: str = "medium",
                     device: Optional[Union[str, device]] = None,
                     in_memory: bool = False,
                     *args, **kwargs
-                     ) -> Union[WhisperTranscriber, WhisperXTranscriber]:
+                     ) -> Union[WhisperTranscriber, FasterWhisperTranscriber]:
    """
    Load whisper model.
@@ -403,7 +434,7 @@ def load_transcriber(model: str = "medium",
                    - 'large-v3'
                    - 'large'
        whisper_type (str):
-                            Type of whisper model to load. "whisper" or "whisperx".
+                            Type of whisper model to load. "whisper" or "faster-whisper".
        download_root (str, optional): Path to download the model.
                                        Defaults to WHISPER_DEFAULT_PATH.
        device (Optional[Union[str, torch.device]], optional):
@@ -414,17 +445,17 @@ def load_transcriber(model: str = "medium",
        kwargs: Additional keyword arguments only to avoid errors.
    Returns:
-        Union[WhisperTranscriber, WhisperXTranscriber]: 
+        Union[WhisperTranscriber, FasterWhisperTranscriber]:
        One of the Whisper variants as Transcrbier object initialized with the specified model.
    """
    if whisper_type.lower() == 'whisper':
        _model = WhisperTranscriber.load_model(
            model, download_root, device, in_memory, *args, **kwargs)
        return _model
-    elif whisper_type.lower() == 'whisperx':
+    elif whisper_type.lower() == 'faster-whisper':
-        _model = WhisperXTranscriber.load_model(
+        _model = FasterWhisperTranscriber.load_model(
            model, download_root, device, *args, **kwargs)
        return _model
    else:
        raise ValueError(f'Model type not recognized, exptected "whisper" '
-                         f'or "whisperx", got {whisper_type}.')
+                         f'or "faster-whisper", got {whisper_type}.')
@@ -1,6 +1,6 @@
 import pytest
 from scraibe import (Transcriber, WhisperTranscriber,
-                     WhisperXTranscriber, load_transcriber)
+                     FasterWhisperTranscriber, load_transcriber)
 import torch
@@ -31,33 +31,33 @@ def test_transcriber(mock_load_model, audio_file, expected_transcription):
@pytest.fixture
 def whisper_instance():
-    return load_transcriber('medium', whisper_type='whisper')
+    return load_transcriber('tiny', whisper_type='whisper')
@pytest.fixture
-def whisperx_instance():
+def faster_whisper_instance():
-    return load_transcriber('medium', whisper_type='whisperx')
+    return load_transcriber('tiny', whisper_type='faster-whisper')
 def test_whisper_base_initialization(whisper_instance):
    assert isinstance(whisper_instance, Transcriber)
-def test_whisperx_base_initialization(whisperx_instance):
+def test_faster_whisper_base_initialization(faster_whisper_instance):
-    assert isinstance(whisperx_instance, Transcriber)
+    assert isinstance(faster_whisper_instance, Transcriber)
 def test_whisper_transcriber_initialization(whisper_instance):
    assert isinstance(whisper_instance, WhisperTranscriber)
-def test_whisperx_transcriber_initialization(whisperx_instance):
+def test_faster_whisper_transcriber_initialization(faster_whisper_instance):
-    assert isinstance(whisperx_instance, WhisperXTranscriber)
+    assert isinstance(faster_whisper_instance, FasterWhisperTranscriber)
 def test_wrong_transcriber_initialization():
    with pytest.raises(ValueError):
-        load_transcriber('medium', whisper_type='wrong_whisper')
+        load_transcriber('tiny', whisper_type='wrong_whisper')
 def test_get_whisper_kwargs():
@@ -73,8 +73,8 @@ def test_whisper_transcribe(whisper_instance):
    assert isinstance(transcript, str)
-def test_whisperx_transcribe(whisperx_instance):
+def test_faster_whisper_transcribe(faster_whisper_instance):
-    model = whisperx_instance
+    model = faster_whisper_instance
    # mocker.patch.object(transcriber_instance.model, 'transcribe', return_value={'Hello, World !'} )
    transcript = model.transcribe('test/audio_test_2.mp4')
    assert isinstance(transcript, str)
@@ -0,0 +1,10 @@
 from os import environ
 environ["AUTOT_CACHE"] = "/mnt/disk1/Projekte/ScrAIbe/tests"
 # environ["PYANNOTE_CACHE"] = "/mnt/disk1/Projekte/ScrAIbe/tests/pyannote"
 # environ["TORCH_HOME"] = "/mnt/disk1/Projekte/ScrAIbe/tests/torch"
 from scraibe import Scraibe
 scraibe = Scraibe(whisper_type = "faster-whisper", whisper_model = "tiny")
 print(scraibe.autotranscribe('/mnt/disk1/Projekte/ScrAIbe/test/audio_test_1.mp4'))