Automatic Speech Recognition
Transformers
PyTorch
Divehi
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use zongxiao/whisper-small-dv with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use zongxiao/whisper-small-dv with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="zongxiao/whisper-small-dv")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("zongxiao/whisper-small-dv") model = AutoModelForSpeechSeq2Seq.from_pretrained("zongxiao/whisper-small-dv", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from zongxiao/whisper-small-dv: direct link, hf CLI and curl.
- Browser
- Download file 4.22 kB
-
https://huggingface.co/zongxiao/whisper-small-dv/resolve/main/training_args.bin
- Command line
-
hf download hf://zongxiao/whisper-small-dv/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/zongxiao/whisper-small-dv/resolve/main/training_args.bin
4.22 kB
- Xet hash:
- df4067c4817c2ab8145556f6d6d22c744d690be80aa6accd93b2698831b52372
- Size of remote file:
- 4.22 kB
- SHA256:
- 4ff46c1d8440091e19ee5e30263af3e61594e37b8bb7248c5d0c4b5a8eb9b3d0
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