Automatic Speech Recognition
Transformers
PyTorch
TensorFlow
JAX
ONNX
Safetensors
whisper
audio
asr
hf-asr-leaderboard
Instructions to use NbAiLab/nb-whisper-tiny-beta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NbAiLab/nb-whisper-tiny-beta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="NbAiLab/nb-whisper-tiny-beta")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("NbAiLab/nb-whisper-tiny-beta") model = AutoModelForSpeechSeq2Seq.from_pretrained("NbAiLab/nb-whisper-tiny-beta", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download onnx/decoder_model.onnx from NbAiLab/nb-whisper-tiny-beta: direct link, hf CLI and curl.
- Browser
- Download file 198 MB
-
https://huggingface.co/NbAiLab/nb-whisper-tiny-beta/resolve/main/onnx/decoder_model.onnx
- Command line
-
hf download hf://NbAiLab/nb-whisper-tiny-beta/onnx/decoder_model.onnx
-
curl -L -o decoder_model.onnx https://huggingface.co/NbAiLab/nb-whisper-tiny-beta/resolve/main/onnx/decoder_model.onnx
198 MB
- Xet hash:
- 6135517c595760b6c8ffc539a1342fd452733e9f217e435c5f5753feff4c3844
- Size of remote file:
- 198 MB
- SHA256:
- b0c608b6def5b51f3dbfea62db4c4cfd09b50d7860cd4719ca4afc244f332b16
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