Automatic Speech Recognition
Transformers
PyTorch
JAX
TensorBoard
ONNX
Safetensors
whisper
audio
asr
hf-asr-leaderboard
Instructions to use NbAiLab/nb-whisper-base-verbatim with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NbAiLab/nb-whisper-base-verbatim with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="NbAiLab/nb-whisper-base-verbatim")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("NbAiLab/nb-whisper-base-verbatim") model = AutoModelForSpeechSeq2Seq.from_pretrained("NbAiLab/nb-whisper-base-verbatim", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 134 Bytes
7724919 | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:2ab35bb04631471ce4a1a039fdc69283aa558598a2a0fabefd3b3918c8b63aee
size 290384497
|