Text Classification
Transformers
Safetensors
multilingual
snt_classifier
feature-extraction
news
topic-classification
multi-label
xlm-roberta
custom_code
Instructions to use sweenk/snt-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sweenk/snt-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="sweenk/snt-classifier", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("sweenk/snt-classifier", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
SNT classifier v0.6
Browse files
README.md
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Built by [Sweenk](https://sweenk.com) to categorize its news feed; released so others can use and
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**Links:** [GitHub — model & training code](https://github.com/sweenk/snt-
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[GitHub — data pipeline](https://github.com/sweenk/snt-data)
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## At a glance
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Built by [Sweenk](https://sweenk.com) to categorize its news feed; released so others can use and
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scrutinize it.
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**Links:** [GitHub — model & training code](https://github.com/sweenk/snt-classification) ·
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[GitHub — data pipeline](https://github.com/sweenk/snt-data)
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## At a glance
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