Instructions to use rasgaard/whisper-tiny.da with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rasgaard/whisper-tiny.da with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="rasgaard/whisper-tiny.da")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("rasgaard/whisper-tiny.da") model = AutoModelForSpeechSeq2Seq.from_pretrained("rasgaard/whisper-tiny.da", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from rasgaard/whisper-tiny.da: direct link, hf CLI and curl.
- Browser
- Download file 231 MB
-
https://huggingface.co/rasgaard/whisper-tiny.da/resolve/main/model.safetensors
- Command line
-
hf download hf://rasgaard/whisper-tiny.da/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/rasgaard/whisper-tiny.da/resolve/main/model.safetensors
231 MB
- Xet hash:
- 6115c70f5f6f975bc4c92cf5800ddf0ed17d1558f9f0920f164f1f2df13c1adc
- Size of remote file:
- 231 MB
- SHA256:
- 627fce3ffd976729b6e82e9ccceedcefc6132b9106f5df4256a95aeaecadb8fc
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