Instructions to use Neroism8422/Text_Classification_10000 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Neroism8422/Text_Classification_10000 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Neroism8422/Text_Classification_10000")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Neroism8422/Text_Classification_10000") model = AutoModelForSequenceClassification.from_pretrained("Neroism8422/Text_Classification_10000") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 498b012653c0722a1f51c821414edf8455a9038321bc87886f6d62518e8d0f16
- Size of remote file:
- 268 MB
- SHA256:
- 60cd76effad4693c43ab7b5a06a6068c5aa64850ac972ed7ad7d55642199c0e5
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