Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
Divehi
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use ahmedbasemdev/whisper-small-dv with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ahmedbasemdev/whisper-small-dv with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="ahmedbasemdev/whisper-small-dv")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("ahmedbasemdev/whisper-small-dv") model = AutoModelForSpeechSeq2Seq.from_pretrained("ahmedbasemdev/whisper-small-dv", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b278f731f3b7d97f72d31180b851e1c72804fe39bc312890169798754e483e1f
- Size of remote file:
- 5.37 kB
- SHA256:
- 3158bdb87727561eec66591f3810d3d0444e87afa8b9be8ba5a7b79a1c4b67f8
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