Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Safetensors
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use Frorozcol/whisper-small-dv with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Frorozcol/whisper-small-dv with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Frorozcol/whisper-small-dv")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Frorozcol/whisper-small-dv") model = AutoModelForSpeechSeq2Seq.from_pretrained("Frorozcol/whisper-small-dv", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ccd2448dfa63b06d761b6aa508ef29e2851fdfd04e48e734d0f27b802e85a85e
- Size of remote file:
- 4.73 kB
- SHA256:
- 065815863ad7ee801aef0dd7b86680e4dc51563f2aa0f632e4d08d7373e35b59
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