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 pytorch_model.bin from SebLih/whisper-SV3: direct link, hf CLI and curl.
- Browser
- Download file 967 MB
-
https://huggingface.co/SebLih/whisper-SV3/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://SebLih/whisper-SV3/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/SebLih/whisper-SV3/resolve/main/pytorch_model.bin
967 MB
- Xet hash:
- e792ad48c70b6a7134211af29966ecfd7a44381ba25311ce0dcb4a2d25ca5134
- Size of remote file:
- 967 MB
- SHA256:
- 94b1a35c37a1f584f8139ef40efcb23d9062a24a88fa80a2fb0d1e053359c57f
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