Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Dutch
whisper
hf-asr-leaderboard
Generated from Trainer
Eval Results (legacy)
Instructions to use AlexMo/improved_whisper_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AlexMo/improved_whisper_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="AlexMo/improved_whisper_model")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("AlexMo/improved_whisper_model") model = AutoModelForSpeechSeq2Seq.from_pretrained("AlexMo/improved_whisper_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from AlexMo/improved_whisper_model: direct link, hf CLI and curl.
- Browser
- Download file 967 MB
-
https://huggingface.co/AlexMo/improved_whisper_model/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://AlexMo/improved_whisper_model/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/AlexMo/improved_whisper_model/resolve/main/pytorch_model.bin
967 MB
- Xet hash:
- 9dfd22524c12a40d7d559c16fb9cd26493533d032940ff5b8d3b30f14bab5ee4
- Size of remote file:
- 967 MB
- SHA256:
- 216c9c655340940924ba4043080fe40654d2bd14046e25baaeb54f8e676c4df0
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