Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use Maimonator/whisper-tiny-en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Maimonator/whisper-tiny-en with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Maimonator/whisper-tiny-en")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Maimonator/whisper-tiny-en") model = AutoModelForSpeechSeq2Seq.from_pretrained("Maimonator/whisper-tiny-en", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Maimonator/whisper-tiny-en: direct link, hf CLI and curl.
- Browser
- Download file 151 MB
-
https://huggingface.co/Maimonator/whisper-tiny-en/resolve/refs%2Fpr%2F1/pytorch_model.bin
- Command line
-
hf download hf://Maimonator/whisper-tiny-en@refs/pr/1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Maimonator/whisper-tiny-en/resolve/refs%2Fpr%2F1/pytorch_model.bin
151 MB
- Xet hash:
- 17d6e9985cd4dda1bf7bc10cb31180be8c3c0a190609bc85069ff892cd291527
- Size of remote file:
- 151 MB
- SHA256:
- 18fb4a51339a2b249da6a71863947005a20fc41b880c42938bcf2fa0284469e9
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