Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Swedish
whisper
hf-asr-leaderboard
Generated from Trainer
Instructions to use SebLih/whisper-SV with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SebLih/whisper-SV with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="SebLih/whisper-SV")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("SebLih/whisper-SV") model = AutoModelForSpeechSeq2Seq.from_pretrained("SebLih/whisper-SV", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from SebLih/whisper-SV: direct link, hf CLI and curl.
- Browser
- Download file 3.64 kB
-
https://huggingface.co/SebLih/whisper-SV/resolve/main/training_args.bin
- Command line
-
hf download hf://SebLih/whisper-SV/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/SebLih/whisper-SV/resolve/main/training_args.bin
3.64 kB
- Xet hash:
- 1b8ccb7baa5738811e5752e7867ba30543aaafc20856671b106832f36d1a5081
- Size of remote file:
- 3.64 kB
- SHA256:
- b54a2e6bafbbeebaa0aeaff3a4d84640a0ddb0acfead0aa35fecd7e95f0080c3
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