Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use mcamara/whisper-tiny-dv with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mcamara/whisper-tiny-dv with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="mcamara/whisper-tiny-dv")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("mcamara/whisper-tiny-dv") model = AutoModelForSpeechSeq2Seq.from_pretrained("mcamara/whisper-tiny-dv", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 129 Bytes
8efcce4 | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:dd294176b1d474a85b7fdb185ffb6207b41ae7176e504b290f9c9bc6d8ea08f7
size 4155
|