Instructions to use orisuchy/Descriptive_Classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use orisuchy/Descriptive_Classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="orisuchy/Descriptive_Classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("orisuchy/Descriptive_Classifier") model = AutoModelForSequenceClassification.from_pretrained("orisuchy/Descriptive_Classifier") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 87fa275f9d3eff80792d8ea47bdc64a2fa9aef7bffac36693ace4ba46d5a4d69
- Size of remote file:
- 504 MB
- SHA256:
- 2c4b7883c9fe2d886e1468ebcc7a09769d1cfc4fe571830870f621d632a11eb4
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