Text Classification
Transformers
TensorFlow
bert
generated_from_keras_callback
text-embeddings-inference
Instructions to use Mingyi/classify_title_subject with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Mingyi/classify_title_subject with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Mingyi/classify_title_subject")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Mingyi/classify_title_subject") model = AutoModelForSequenceClassification.from_pretrained("Mingyi/classify_title_subject") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 280210c9e5546ed5feb31614602518984f8c90f86342ec19c8ea17587a212ed7
- Size of remote file:
- 712 MB
- SHA256:
- c2907ce89ca81a850bb2c8e29b108aebbbb83d6bd55afa85bde8359d4673c576
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