Automatic Speech Recognition
Transformers
PyTorch
TensorFlow
JAX
TensorBoard
ONNX
Safetensors
whisper
audio
asr
hf-asr-leaderboard
Instructions to use NbAiLabBeta/nb-whisper-tiny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NbAiLabBeta/nb-whisper-tiny with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="NbAiLabBeta/nb-whisper-tiny")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("NbAiLabBeta/nb-whisper-tiny") model = AutoModelForSpeechSeq2Seq.from_pretrained("NbAiLabBeta/nb-whisper-tiny", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Update onnx/vocab.json
8e8df8f -
Update onnx/tokenizer.json
0b12521 -
Update onnx/tokenizer_config.json
64a5fd5 -
Update onnx/special_tokens_map.json
1a12fab -
Update onnx/preprocessor_config.json
74ecb69 -
Update onnx/normalizer.json
08ce134 -
Update onnx/merges.txt
d4f53ad -
Update onnx/generation_config.json
56bb1f9 -
Update onnx/encoder_model.onnx
a13c257 -
Update onnx/decoder_with_past_model.onnx
b89b921 -
Update onnx/decoder_model.onnx
3ef67a6 -
Update onnx/config.json
a2cb788 -
Update onnx/added_tokens.json
7059f42