Instructions to use procit007/Classification_Model_june23_clustering with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use procit007/Classification_Model_june23_clustering with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="procit007/Classification_Model_june23_clustering")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("procit007/Classification_Model_june23_clustering") model = AutoModelForSequenceClassification.from_pretrained("procit007/Classification_Model_june23_clustering") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 735d2eb21bc3936d32d921668cd8b808c94c9e8bf2086364507d1561c345cf33
- Size of remote file:
- 438 MB
- SHA256:
- 24e9dc1738e0ce73a5bf0f9ac0409b92c39292721fc327d4f0a53490732e00d7
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