Instructions to use prajjwal1/bert-small-mnli with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use prajjwal1/bert-small-mnli with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="prajjwal1/bert-small-mnli")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("prajjwal1/bert-small-mnli") model = AutoModelForSequenceClassification.from_pretrained("prajjwal1/bert-small-mnli") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2571d2d8d897a7ec02979e3d595f62ef5b3d5a14ef0735cea9e559269b10758a
- Size of remote file:
- 115 MB
- SHA256:
- c38c204996c136a6ea48a0494cdbf9c971300557f339d0c8f31218d20e05a6ed
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