Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
Divehi
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use pedrottic/whisper-small-dv with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pedrottic/whisper-small-dv with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="pedrottic/whisper-small-dv")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("pedrottic/whisper-small-dv") model = AutoModelForSpeechSeq2Seq.from_pretrained("pedrottic/whisper-small-dv", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9aa97eecb80341026c08d175f86b8490b55bc3ae7058469fab46d77d4fc2b26d
- Size of remote file:
- 5.56 kB
- SHA256:
- 8d77380c495ad86aa81f3e549c491419491ca68039143a1990b2045bdb9da09c
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