Instructions to use DeepLoading/slang-stt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DeepLoading/slang-stt with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="DeepLoading/slang-stt")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("DeepLoading/slang-stt") model = AutoModelForCTC.from_pretrained("DeepLoading/slang-stt", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 05472a7f26a1e5fe60c85fe9638feb3e2e6d602191bac1740ca7c6e1e05cbe7c
- Size of remote file:
- 3.85 GB
- SHA256:
- 33c3fbd01111f921e39aeef286c090835142f938d752b0b7e828e19a3340b9b8
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