Instructions to use Neroism8422/Text_Classification_100 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Neroism8422/Text_Classification_100 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Neroism8422/Text_Classification_100")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Neroism8422/Text_Classification_100") model = AutoModelForSequenceClassification.from_pretrained("Neroism8422/Text_Classification_100") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e36d094b61eb2a1f3f2ff476f0a64cb0d1280f550450a56c9c0dcf5e674e297c
- Size of remote file:
- 268 MB
- SHA256:
- b8dc4e7fe6bb0e5056bcef4a3b0db079d24d1b9cabb3a5de5f80183f88319fae
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