Instructions to use ModelTC/bart-base-mnli with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ModelTC/bart-base-mnli with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ModelTC/bart-base-mnli")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ModelTC/bart-base-mnli") model = AutoModelForSequenceClassification.from_pretrained("ModelTC/bart-base-mnli") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b705a0b2e73e3135b18a70d9d42c6ec4960cac33c499c566d81c96c77252c7d6
- Size of remote file:
- 1.12 GB
- SHA256:
- a636fceca81567feda9a97fbe87c300bda3efc94e30c8a6536c17722054d1c3b
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