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 training_args.bin from Inayat/whisper_small_fine_tuning: direct link, hf CLI and curl.
- Browser
- Download file 4.16 kB
-
https://huggingface.co/Inayat/whisper_small_fine_tuning/resolve/main/training_args.bin
- Command line
-
hf download hf://Inayat/whisper_small_fine_tuning/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Inayat/whisper_small_fine_tuning/resolve/main/training_args.bin
4.16 kB
- Xet hash:
- 23d49e274d51b282022d544d67fb6664314be0877fb887e2b8eb8ff133c96678
- Size of remote file:
- 4.16 kB
- SHA256:
- 5a48910caa5bfd8d55c2f0b21f36542578c291113f541d988925e023dd0ac329
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