Instructions to use data-corentinv/whisper-tiny-fr-cv with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use data-corentinv/whisper-tiny-fr-cv with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="data-corentinv/whisper-tiny-fr-cv")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("data-corentinv/whisper-tiny-fr-cv") model = AutoModelForSpeechSeq2Seq.from_pretrained("data-corentinv/whisper-tiny-fr-cv", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from data-corentinv/whisper-tiny-fr-cv: direct link, hf CLI and curl.
- Browser
- Download file 5.37 kB
-
https://huggingface.co/data-corentinv/whisper-tiny-fr-cv/resolve/main/training_args.bin
- Command line
-
hf download hf://data-corentinv/whisper-tiny-fr-cv/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/data-corentinv/whisper-tiny-fr-cv/resolve/main/training_args.bin
5.37 kB
- Xet hash:
- 032f5d33a47a4c7ef141dcb28914e769ef583cf6a090001b8389cddbd0eec5ba
- Size of remote file:
- 5.37 kB
- SHA256:
- 03029060bfe8fd18da602766be8c439fadbc183505dfc9f9ef85a96f670e27b2
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