Instructions to use princeton-nlp/bert_base_mnli_1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use princeton-nlp/bert_base_mnli_1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="princeton-nlp/bert_base_mnli_1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("princeton-nlp/bert_base_mnli_1") model = AutoModelForSequenceClassification.from_pretrained("princeton-nlp/bert_base_mnli_1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 23c2552bd63b7355fcff5d07d84ff12c024d701f3d29c064125aadaa7bd284c6
- Size of remote file:
- 438 MB
- SHA256:
- 2dee800b9302a1f62db5dbb1739c516d90b4a8b89eb4d814ab54a23fbc65a594
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