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 training_args.bin from AlexMo/improved_whisper_model: direct link, hf CLI and curl.
- Browser
- Download file 3.64 kB
-
https://huggingface.co/AlexMo/improved_whisper_model/resolve/refs%2Fpr%2F1/training_args.bin
- Command line
-
hf download hf://AlexMo/improved_whisper_model@refs/pr/1/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/AlexMo/improved_whisper_model/resolve/refs%2Fpr%2F1/training_args.bin
3.64 kB
- Xet hash:
- bdeef713d31a75b45058fd8a4e6413afe9f7a606b9219d81c1137b28197dbc20
- Size of remote file:
- 3.64 kB
- SHA256:
- c0a8de8b22534849ffeb3eb5a8844c08c3b8ce510d512616f35437e83a7f0c46
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