Instructions to use daveni/whisper-tiny-commonvoice_v11-de with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use daveni/whisper-tiny-commonvoice_v11-de with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="daveni/whisper-tiny-commonvoice_v11-de")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("daveni/whisper-tiny-commonvoice_v11-de") model = AutoModelForSpeechSeq2Seq.from_pretrained("daveni/whisper-tiny-commonvoice_v11-de", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from daveni/whisper-tiny-commonvoice_v11-de: direct link, hf CLI and curl.
- Browser
- Download file 3.58 kB
-
https://huggingface.co/daveni/whisper-tiny-commonvoice_v11-de/resolve/main/training_args.bin
- Command line
-
hf download hf://daveni/whisper-tiny-commonvoice_v11-de/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/daveni/whisper-tiny-commonvoice_v11-de/resolve/main/training_args.bin
3.58 kB
- Xet hash:
- 0d5956214da4767f4cc08cddbecf8517cd3b9ba88f4c34bc0972613281f8ddab
- Size of remote file:
- 3.58 kB
- SHA256:
- f159ccb7288a54dfed87b874f87351a399ec44767aecf8418ef573cb5755134b
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