Instructions to use AyoubChLin/Stable_BART_MNLI_CNN with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AyoubChLin/Stable_BART_MNLI_CNN with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AyoubChLin/Stable_BART_MNLI_CNN")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AyoubChLin/Stable_BART_MNLI_CNN") model = AutoModelForSequenceClassification.from_pretrained("AyoubChLin/Stable_BART_MNLI_CNN") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 59fd0a1cc8b67bc04c92f221a389821221017f7e11d205c61d562593add73ce7
- Size of remote file:
- 1.63 GB
- SHA256:
- 98c0cb10d73d227a4c291e9e9097fde908a22886a48476a4c548e1575a81ac86
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