Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use GFazzito/whisper-tiny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use GFazzito/whisper-tiny with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="GFazzito/whisper-tiny")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("GFazzito/whisper-tiny") model = AutoModelForSpeechSeq2Seq.from_pretrained("GFazzito/whisper-tiny", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from GFazzito/whisper-tiny: direct link, hf CLI and curl.
- Browser
- Download file 75.6 MB
-
https://huggingface.co/GFazzito/whisper-tiny/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://GFazzito/whisper-tiny/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/GFazzito/whisper-tiny/resolve/main/pytorch_model.bin
75.6 MB
- Xet hash:
- 1d861097d03a5ce211bbdd0cf3445dc0313cb7673dec99a34e3de0ed5699de5e
- Size of remote file:
- 75.6 MB
- SHA256:
- 9aa7bdc1aefb097baeb7c4753389039bedb8b427e418c738305b5cb3bc666419
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