Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
Danish
whisper
hf-asr-leaderboard
Generated from Trainer
Eval Results (legacy)
Instructions to use JulieHinge/whisper-medium-ftspeech with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JulieHinge/whisper-medium-ftspeech with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="JulieHinge/whisper-medium-ftspeech")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("JulieHinge/whisper-medium-ftspeech") model = AutoModelForSpeechSeq2Seq.from_pretrained("JulieHinge/whisper-medium-ftspeech", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9e37613501b4ae51515d93be15d356b203197eff59a794a49c51120984f32297
- Size of remote file:
- 5.5 kB
- SHA256:
- 1b5ccc4de150fab7e155a9075551f88d2ce53a07038e84b035cbb8a3c76d66fd
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