Instructions to use gechim/metadata-cls_15_10 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gechim/metadata-cls_15_10 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="gechim/metadata-cls_15_10")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("gechim/metadata-cls_15_10") model = AutoModelForSequenceClassification.from_pretrained("gechim/metadata-cls_15_10") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a5224c7d20215e3aaa452c732cfbc34e3b28f1344c8a1a12d2bf4596a594c591
- Size of remote file:
- 5.18 kB
- SHA256:
- 8ef3434a86578a825cfa0100e171d6ff2d518efbd36b316f2d161db8e18a6099
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