Instructions to use danasone/rubert-tiny-speech with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use danasone/rubert-tiny-speech with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="danasone/rubert-tiny-speech")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("danasone/rubert-tiny-speech") model = AutoModelForTokenClassification.from_pretrained("danasone/rubert-tiny-speech", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f5bd5b54c4a18a943ade055f178369aabe56d8133857f22fb0ee35b7f95f08f7
- Size of remote file:
- 116 MB
- SHA256:
- d102ec0adfe5a65aca0df7857242fc8d7133419dc1e1f6120be37ceb767f4923
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