Instructions to use Mitradn/whisper-cap with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Mitradn/whisper-cap with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Mitradn/whisper-cap")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Mitradn/whisper-cap") model = AutoModelForSpeechSeq2Seq.from_pretrained("Mitradn/whisper-cap") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a2d8c94d5389eacff5411aec0d30c35c3dc840017e75bb81c6300ba3260a3ec0
- Size of remote file:
- 4.86 kB
- SHA256:
- c497c581e2608e243d17ab04d4f59fc7c2d3a213af09a44e0de58f2a0ef41722
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