Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Belarusian
whisper
whisper-event
Generated from Trainer
Eval Results (legacy)
Instructions to use ales/whisper-tiny-be-test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ales/whisper-tiny-be-test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="ales/whisper-tiny-be-test")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("ales/whisper-tiny-be-test") model = AutoModelForSpeechSeq2Seq.from_pretrained("ales/whisper-tiny-be-test", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 706 Bytes
bae08f8 1404413 bae08f8 1404413 bae08f8 1404413 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 | sudo add-apt-repository -y ppa:jonathonf/ffmpeg-4
sudo apt update
sudo apt install -y ffmpeg
sudo apt-get install git-lfs
sudo apt-get install tmux
cd ~
echo "executing env setup from $(pwd)"
python3 -m venv ~/python_venvs/hf_env
source ~/python_venvs/hf_env/bin/activate
echo "source ~/python_venvs/hf_env/bin/activate" >> ~/.bashrc
git clone https://github.com/yks72p/whisper-finetuning-be
pip install -r ~/whisper-finetuning-be/requirements.txt
git config --global credential.helper store
huggingface-cli login
echo "env setup"
echo "! PLEASE LOGIN INTO GIT TO BE ABLE TO PUSH TO HF HUB !"
echo "> git config --globase user.name <user_name>"
echo "> git config --globase user.email <user_email>"
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