Instructions to use Softechlb/articles_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Softechlb/articles_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Softechlb/articles_classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Softechlb/articles_classification") model = AutoModelForSequenceClassification.from_pretrained("Softechlb/articles_classification") - Notebooks
- Google Colab
- Kaggle
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README.md
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```python
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from transformers import AutoTokenizer, AutoModelForSequenceClassification
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tokenizer = AutoTokenizer.from_pretrained("
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model = AutoModelForSequenceClassification.from_pretrained("
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# Tokenize input text
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text = "This is an example CNN news article about politics."
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```python
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from transformers import AutoTokenizer, AutoModelForSequenceClassification
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tokenizer = AutoTokenizer.from_pretrained("Softechlb/articles_classification")
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model = AutoModelForSequenceClassification.from_pretrained("Softechlb/articles_classification")
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# Tokenize input text
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text = "This is an example CNN news article about politics."
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