Instructions to use fractalego/personal-whisper-small.en-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fractalego/personal-whisper-small.en-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="fractalego/personal-whisper-small.en-model")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("fractalego/personal-whisper-small.en-model") model = AutoModelForSpeechSeq2Seq.from_pretrained("fractalego/personal-whisper-small.en-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from fractalego/personal-whisper-small.en-model: direct link, hf CLI and curl.
- Browser
- Download file 967 MB
-
https://huggingface.co/fractalego/personal-whisper-small.en-model/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://fractalego/personal-whisper-small.en-model/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/fractalego/personal-whisper-small.en-model/resolve/main/pytorch_model.bin
967 MB
- Xet hash:
- 10521b2a4585ebaf9818014e23f27226f8aacd2ad899f3a1365062625587b237
- Size of remote file:
- 967 MB
- SHA256:
- 2f633893e47fe37665929704cd66adb9b6f13bff804caaf58ef7b8c31b147b6a
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