Instructions to use aloxatel/bert-base-mnli with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aloxatel/bert-base-mnli with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="aloxatel/bert-base-mnli")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("aloxatel/bert-base-mnli") model = AutoModelForSequenceClassification.from_pretrained("aloxatel/bert-base-mnli") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 80be56cfca921268c5346ff2735f489415d7890023bcc8e699d8c9f19a67533e
- Size of remote file:
- 438 MB
- SHA256:
- ad772e64c2e0cc7eedf23bec4dabdc587ce3dea831d9d002a25652d0bd56e7dd
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