Instructions to use DataMuncher-Labs/SC-100k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DataMuncher-Labs/SC-100k with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="DataMuncher-Labs/SC-100k")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("DataMuncher-Labs/SC-100k", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b064c0c361c756dd65627a87e2566fe6718764c7dc5b00346fbb5c5b41554d71
- Size of remote file:
- 1.24 MB
- SHA256:
- 90b1cef69f8be0c942453f8ecbc53b0b92798bd837049b2b7122dcd1772f7d35
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