Instructions to use fahdmirzac/whisper-small-ur with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fahdmirzac/whisper-small-ur with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="fahdmirzac/whisper-small-ur")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("fahdmirzac/whisper-small-ur") model = AutoModelForSpeechSeq2Seq.from_pretrained("fahdmirzac/whisper-small-ur", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from fahdmirzac/whisper-small-ur: direct link, hf CLI and curl.
- Browser
- Download file 5.24 kB
-
https://huggingface.co/fahdmirzac/whisper-small-ur/resolve/main/training_args.bin
- Command line
-
hf download hf://fahdmirzac/whisper-small-ur/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/fahdmirzac/whisper-small-ur/resolve/main/training_args.bin
5.24 kB
- Xet hash:
- 748b4a098c4bcb1540f401cefc1798e2ad7d1339d3246c017fb06ae710b8165a
- Size of remote file:
- 5.24 kB
- SHA256:
- 6a3d2176ef3341c4e466e8fa8e54be72e600ea68736a7f332f4bfc476c77ce5b
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