Instructions to use stackintel/whisper-small-ro with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use stackintel/whisper-small-ro with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="stackintel/whisper-small-ro")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("stackintel/whisper-small-ro") model = AutoModelForSpeechSeq2Seq.from_pretrained("stackintel/whisper-small-ro", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from stackintel/whisper-small-ro: direct link, hf CLI and curl.
- Browser
- Download file 3.63 kB
-
https://huggingface.co/stackintel/whisper-small-ro/resolve/main/training_args.bin
- Command line
-
hf download hf://stackintel/whisper-small-ro/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/stackintel/whisper-small-ro/resolve/main/training_args.bin
3.63 kB
- Xet hash:
- b117f9999c6fa0c614c86d14866171021227020a202ce5ae2f4dc9c3c22ab9bc
- Size of remote file:
- 3.63 kB
- SHA256:
- 4c7d2511af6e4eb470b87f69ae731ec9af9cc3445fea8443a2bd0709e1f3af19
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