Instructions to use AyoubChLin/BART_Company_Documents_classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AyoubChLin/BART_Company_Documents_classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AyoubChLin/BART_Company_Documents_classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AyoubChLin/BART_Company_Documents_classifier") model = AutoModelForSequenceClassification.from_pretrained("AyoubChLin/BART_Company_Documents_classifier") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 294904239391d158697d6cbad5cd2f1fa2769bb01ccb38dcfd58781d2315092a
- Size of remote file:
- 1.63 GB
- SHA256:
- 09d801b7681a917af34352143d85c020e9445aa30afed57d016693ce718ea9a9
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