Instructions to use Yapeng/whisper-small-pt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Yapeng/whisper-small-pt with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Yapeng/whisper-small-pt")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Yapeng/whisper-small-pt") model = AutoModelForSpeechSeq2Seq.from_pretrained("Yapeng/whisper-small-pt", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Yapeng/whisper-small-pt: direct link, hf CLI and curl.
- Browser
- Download file 3.5 kB
-
https://huggingface.co/Yapeng/whisper-small-pt/resolve/main/training_args.bin
- Command line
-
hf download hf://Yapeng/whisper-small-pt/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Yapeng/whisper-small-pt/resolve/main/training_args.bin
3.5 kB
- Xet hash:
- 1f627138e051b5cc1be33e0545d2452d498e0edf51d0759925be3d16f3134e6c
- Size of remote file:
- 3.5 kB
- SHA256:
- 1ac204e2762aaab2d3f59ce61d73b8a7fb5e1f9724f92d59b71383f7a17e163f
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