Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
Divehi
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use smallsuper/whisper-small-dv with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use smallsuper/whisper-small-dv with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="smallsuper/whisper-small-dv")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("smallsuper/whisper-small-dv") model = AutoModelForSpeechSeq2Seq.from_pretrained("smallsuper/whisper-small-dv", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 129 Bytes
821f2f3 | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:f50b4d033ea585ea37ea1a4897813d39ede85317d273096f36aaed501af21c47
size 6033
|