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 training_args.bin from GFazzito/whisper-tiny: direct link, hf CLI and curl.
- Browser
- Download file 4.22 kB
-
https://huggingface.co/GFazzito/whisper-tiny/resolve/main/training_args.bin
- Command line
-
hf download hf://GFazzito/whisper-tiny/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/GFazzito/whisper-tiny/resolve/main/training_args.bin
4.22 kB
- Xet hash:
- 53e2994ae8626de4c5d13cd51294156f5f003cac059ef78e6cd1cfb090ad3c99
- Size of remote file:
- 4.22 kB
- SHA256:
- 038a19f8ae45665ef96e8ac8b8402c933ac71427b4cb72e8f3319f6c4e95a8aa
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