Instructions to use ruisp/whisper-small-dv with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ruisp/whisper-small-dv with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="ruisp/whisper-small-dv")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("ruisp/whisper-small-dv") model = AutoModelForSpeechSeq2Seq.from_pretrained("ruisp/whisper-small-dv", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from ruisp/whisper-small-dv: direct link, hf CLI and curl.
- Browser
- Download file 151 MB
-
https://huggingface.co/ruisp/whisper-small-dv/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://ruisp/whisper-small-dv/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/ruisp/whisper-small-dv/resolve/main/pytorch_model.bin
151 MB
- Xet hash:
- 811a2035690ad74c5772c6609bfd28980d9054ffa5e3302256e05cd0f0c40926
- Size of remote file:
- 151 MB
- SHA256:
- 5a3de0940a559c34a705209a08486ce50dc7e32d8dd8f74f9f494a4b0a96fa0a
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