Instructions to use Inayat/whisper_small_fine_tuning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Inayat/whisper_small_fine_tuning with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Inayat/whisper_small_fine_tuning")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Inayat/whisper_small_fine_tuning") model = AutoModelForSpeechSeq2Seq.from_pretrained("Inayat/whisper_small_fine_tuning", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Inayat/whisper_small_fine_tuning: direct link, hf CLI and curl.
- Browser
- Download file 967 MB
-
https://huggingface.co/Inayat/whisper_small_fine_tuning/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Inayat/whisper_small_fine_tuning/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Inayat/whisper_small_fine_tuning/resolve/main/pytorch_model.bin
967 MB
- Xet hash:
- c78950e4ff3ffe5f8b393c1d6fe4203fb443ab0c7d77c69f69cb17f31ae2cd2e
- Size of remote file:
- 967 MB
- SHA256:
- 7bfd602979cbd7837c23e462f58a15e1459c903546034e31cca3edc7a6b08ff6
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