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") - Notebooks
- Google Colab
- Kaggle
| 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>" | |