Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
Divehi
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use ibbeh/whisper-small-dv-second with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ibbeh/whisper-small-dv-second with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="ibbeh/whisper-small-dv-second")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("ibbeh/whisper-small-dv-second") model = AutoModelForSpeechSeq2Seq.from_pretrained("ibbeh/whisper-small-dv-second", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from ibbeh/whisper-small-dv-second: direct link, hf CLI and curl.
- Browser
- Download file 5.43 kB
-
https://huggingface.co/ibbeh/whisper-small-dv-second/resolve/main/training_args.bin
- Command line
-
hf download hf://ibbeh/whisper-small-dv-second/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/ibbeh/whisper-small-dv-second/resolve/main/training_args.bin
5.43 kB
- Xet hash:
- 0bc47a43e1995edec5bd54726154191a25ef5e9db55d1eff5ce0ebfa32d00274
- Size of remote file:
- 5.43 kB
- SHA256:
- 6dd90d418a05ac6a988787f9513380b5177c8068728180579ca8fce9ccc563dd
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