Instructions to use pfe24/temp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pfe24/temp with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="pfe24/temp")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("pfe24/temp") model = AutoModelForSpeechSeq2Seq.from_pretrained("pfe24/temp", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from pfe24/temp: direct link, hf CLI and curl.
- Browser
- Download file 5.24 kB
-
https://huggingface.co/pfe24/temp/resolve/main/training_args.bin
- Command line
-
hf download hf://pfe24/temp/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/pfe24/temp/resolve/main/training_args.bin
5.24 kB
- Xet hash:
- 44b79d8b378f4cd461a3e4f1d2095be42d261295367d74713da53f8e77d32944
- Size of remote file:
- 5.24 kB
- SHA256:
- 7729a4fa90192d1494e0285e4324ed432d5e4676c53b74c2ccd4ca6b31d2beb8
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