Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use Ola172/article_classification_modelv12 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ola172/article_classification_modelv12 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Ola172/article_classification_modelv12")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Ola172/article_classification_modelv12") model = AutoModelForSequenceClassification.from_pretrained("Ola172/article_classification_modelv12", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- dc1d66898096597a6c99a5e4ab29f1b0fe51471897209dfb791e0752702cd213
- Size of remote file:
- 541 MB
- SHA256:
- 5c38cf34600eb0102dfe792af53bdc771076962a418fe617118748d2c088580d
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