Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use ruisp/whisper-tiny-ft-polyai with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ruisp/whisper-tiny-ft-polyai with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="ruisp/whisper-tiny-ft-polyai")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("ruisp/whisper-tiny-ft-polyai") model = AutoModelForSpeechSeq2Seq.from_pretrained("ruisp/whisper-tiny-ft-polyai", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from ruisp/whisper-tiny-ft-polyai: direct link, hf CLI and curl.
- Browser
- Download file 151 MB
-
https://huggingface.co/ruisp/whisper-tiny-ft-polyai/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://ruisp/whisper-tiny-ft-polyai/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/ruisp/whisper-tiny-ft-polyai/resolve/main/pytorch_model.bin
151 MB
- Xet hash:
- bcfbd87f196ba3d886551cf7dd50e73fbb10d6de9c02803a4ac455ecb8898a21
- Size of remote file:
- 151 MB
- SHA256:
- a7c85510b5f373e291700075002f7e3529d16429b79c62e0eea166bf504a7c8f
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