Text Classification
Transformers
PyTorch
TensorBoard
Safetensors
distilbert
text-embeddings-inference
Instructions to use ebrigham/EYY-Topic-Classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ebrigham/EYY-Topic-Classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ebrigham/EYY-Topic-Classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ebrigham/EYY-Topic-Classification") model = AutoModelForSequenceClassification.from_pretrained("ebrigham/EYY-Topic-Classification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6a2a3e727f6d367effeab916dc83622170460ff7e03470e6ea263da87bafdc94
- Size of remote file:
- 268 MB
- SHA256:
- a8341e71cf24a6472be07924b2a4189974c992bf8143e556f17b1be4a66965fb
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