Automatic Speech Recognition
Transformers
PyTorch
JAX
TensorBoard
Danish
whisper
Generated from Trainer
hf-asr-leaderboard
whisper-event
Eval Results (legacy)
Instructions to use caoldr/whisper-medium-da with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use caoldr/whisper-medium-da with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="caoldr/whisper-medium-da")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("caoldr/whisper-medium-da") model = AutoModelForSpeechSeq2Seq.from_pretrained("caoldr/whisper-medium-da", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from caoldr/whisper-medium-da: direct link, hf CLI and curl.
- Browser
- Download file 3.06 GB
-
https://huggingface.co/caoldr/whisper-medium-da/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://caoldr/whisper-medium-da/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/caoldr/whisper-medium-da/resolve/main/flax_model.msgpack
3.06 GB
- Xet hash:
- 05060ea3bb0953d20b786873794ecb2bcb150dfaa292075cbffafe9206b7d146
- Size of remote file:
- 3.06 GB
- SHA256:
- 307f44cd07aa55d4fcb4a8ba009c5bce20bf05c62680d51c6172358b5b791159
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