Instructions to use marinone94/whisper-tiny-sv with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use marinone94/whisper-tiny-sv with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="marinone94/whisper-tiny-sv")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("marinone94/whisper-tiny-sv") model = AutoModelForSpeechSeq2Seq.from_pretrained("marinone94/whisper-tiny-sv") - Notebooks
- Google Colab
- Kaggle
| FROM 763104351884.dkr.ecr.eu-west-1.amazonaws.com/huggingface-pytorch-training:1.10.2-transformers4.17.0-gpu-py38-cu113-ubuntu20.04 as DLC | |
| # RUN apt-get update && apt-get install software-properties-common -y && apt-get update | |
| # RUN add-apt-repository -y ppa:jonathonf/ffmpeg-4 | |
| # RUN apt update | |
| # RUN apt install -y ffmpeg | |
| RUN apt-get install git-lfs | |
| COPY ./requirements.txt . | |
| RUN pip install --timeout=60 -r requirements.txt | |
| RUN apt update && apt-get install libsndfile1 -y | |
| RUN echo $(pip freeze) | md5sum | cut -d ' ' -f 1 >> code_version.txt | |
| ARG REPO_URL | |
| ARG CACHEBUST | |
| RUN echo ${CACHEBUST} | |
| RUN git clone $REPO_URL | |
| RUN workdir=/$(basename $REPO_URL) | |
| WORKDIR $workdir |