Instructions to use slprl/WhiStress with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use slprl/WhiStress with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="slprl/WhiStress")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("slprl/WhiStress", dtype="auto") - Notebooks
- Google Colab
- Kaggle
Add pipeline tag and library name
Browse filesThis PR improves the model card by adding the `pipeline_tag` and `library_name`, ensuring people can find it more easily.
README.md
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datasets:
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- slprl/TinyStress-15K
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# WhiStress Model
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---
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datasets:
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- slprl/TinyStress-15K
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license: cc-by-nc-4.0
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library_name: transformers
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pipeline_tag: automatic-speech-recognition
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# WhiStress Model
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