Automatic Speech Recognition
Transformers
PyTorch
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use ruisp/whisper-tiny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ruisp/whisper-tiny with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="ruisp/whisper-tiny")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("ruisp/whisper-tiny") model = AutoModelForSpeechSeq2Seq.from_pretrained("ruisp/whisper-tiny", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from ruisp/whisper-tiny: direct link, hf CLI and curl.
- Browser
- Download file 151 MB
-
https://huggingface.co/ruisp/whisper-tiny/resolve/refs%2Fpr%2F1/pytorch_model.bin
- Command line
-
hf download hf://ruisp/whisper-tiny@refs/pr/1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/ruisp/whisper-tiny/resolve/refs%2Fpr%2F1/pytorch_model.bin
151 MB
- Xet hash:
- 37bc3c4a9075fc03041784a01a85fc4dc6606f75d8e46f58bc391f398ebde586
- Size of remote file:
- 151 MB
- SHA256:
- 41c420256b1bea6090acef63e148e5fe101295dac40370f0d10317b7bd0e71f4
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