Instructions to use hts98/whisper-tiny-paper with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hts98/whisper-tiny-paper with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="hts98/whisper-tiny-paper")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("hts98/whisper-tiny-paper") model = AutoModelForSpeechSeq2Seq.from_pretrained("hts98/whisper-tiny-paper", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from hts98/whisper-tiny-paper: direct link, hf CLI and curl.
- Browser
- Download file 4.16 kB
-
https://huggingface.co/hts98/whisper-tiny-paper/resolve/main/training_args.bin
- Command line
-
hf download hf://hts98/whisper-tiny-paper/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/hts98/whisper-tiny-paper/resolve/main/training_args.bin
4.16 kB
- Xet hash:
- 9d3c8175f16a7e9884d718de740bd9f4e7b522dceb31834920a2618cfbd6ed20
- Size of remote file:
- 4.16 kB
- SHA256:
- 0e7c62aabc4c6e96e6c5a0376f051c53651d07ecf3ab0445e894f4a8253c31e6
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