Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Swedish
whisper
hf-asr-leaderboard
Generated from Trainer
Instructions to use SebLih/whisper-SV3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SebLih/whisper-SV3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="SebLih/whisper-SV3")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("SebLih/whisper-SV3") model = AutoModelForSpeechSeq2Seq.from_pretrained("SebLih/whisper-SV3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from SebLih/whisper-SV3: direct link, hf CLI and curl.
- Browser
- Download file 3.64 kB
-
https://huggingface.co/SebLih/whisper-SV3/resolve/main/training_args.bin
- Command line
-
hf download hf://SebLih/whisper-SV3/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/SebLih/whisper-SV3/resolve/main/training_args.bin
3.64 kB
- Xet hash:
- ab93cad8f0469866440c2615f44a95a17eeef935586274b930677ce3b482197e
- Size of remote file:
- 3.64 kB
- SHA256:
- 9e6ebd9e297e1ab1a4fe1fc7d19ff45c3d2bb7e78a55f24cb5e148df10df8aa4
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