Automatic Speech Recognition
Transformers
PyTorch
JAX
TensorBoard
ONNX
Safetensors
whisper
audio
asr
hf-asr-leaderboard
Instructions to use NbAiLabBeta/nb-whisper-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NbAiLabBeta/nb-whisper-small with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="NbAiLabBeta/nb-whisper-small")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("NbAiLabBeta/nb-whisper-small") model = AutoModelForSpeechSeq2Seq.from_pretrained("NbAiLabBeta/nb-whisper-small") - Notebooks
- Google Colab
- Kaggle
| pip install "optimum[exporters]>=1.14.1" tensorflow | |
| git lfs track *.onnx* | |
| python << END | |
| from transformers import WhisperForConditionalGeneration, TFWhisperForConditionalGeneration, WhisperTokenizerFast | |
| import shutil | |
| # Backup generation_config.json - this is for tensorflow only, but at the moment that is causing errors. | |
| # shutil.copyfile('./generation_config.json', './generation_config_backup.json') | |
| print("Saving model to PyTorch...", end=" ") | |
| model = WhisperForConditionalGeneration.from_pretrained("./", from_flax=True) | |
| model.save_pretrained("./", safe_serialization=True) | |
| model.save_pretrained("./", safe_serialization=False, max_shard_size="10000MB") | |
| print("Done.") | |
| #print("Saving model to TensorFlow...", end=" ") | |
| #tf_model = TFWhisperForConditionalGeneration.from_pretrained("./") | |
| #tf_model.save_pretrained("./") | |
| #print("Done.") | |
| # Restore the backup of generation_config.json | |
| #shutil.move('./generation_config_backup.json', './generation_config.json') | |
| print("Saving model to ONNX...", end=" ") | |
| from optimum.onnxruntime import ORTModelForSpeechSeq2Seq | |
| ort_model = ORTModelForSpeechSeq2Seq.from_pretrained("./", export=True) | |
| ort_model.save_pretrained("./onnx") | |
| print("Done") | |
| END | |
| echo "Saving model to CTranslate..." | |
| ct2-transformers-converter --model . --output_dir ct2 --force | |
| cp ct2/model.bin . | |
| cp ct2/vocabulary.json . | |
| cp config.json config_hf.json | |
| jq -s '.[0] * .[1]' ct2/config.json config_hf.json > config.json | |
| echo "Done" | |
| echo "Saving model to GGML (whisper.cpp)..." | |
| wget -O convert-h5-to-ggml.py "https://raw.githubusercontent.com/NbAiLab/nb-whisper/main/convert-h5-to-ggml.py" | |
| mkdir -p whisper/assets | |
| wget -O whisper/assets/mel_filters.npz "https://github.com/openai/whisper/raw/c5d42560760a05584c1c79546a098287e5a771eb/whisper/assets/mel_filters.npz" | |
| python ./convert-h5-to-ggml.py ./ ./ ./ | |
| rm ./convert-h5-to-ggml.py | |
| rm -rf ./whisper | |
| echo "Done" | |
| echo "Quantizing GGML model..." | |
| git clone --depth 1 https://github.com/ggerganov/whisper.cpp --branch v1.5.1 | |
| cd whisper.cpp/ | |
| make -j 32 | |
| make quantize -j 32 | |
| ./quantize ../ggml-model.bin ../ggml-model-q5_0.bin q5_0 | |
| cd .. | |
| rm -rf whisper.cpp | |
| echo "Done" | |