Instructions to use princeton-nlp/bert_base_sst2_1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use princeton-nlp/bert_base_sst2_1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="princeton-nlp/bert_base_sst2_1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("princeton-nlp/bert_base_sst2_1") model = AutoModelForSequenceClassification.from_pretrained("princeton-nlp/bert_base_sst2_1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 11233a92539b3a48a3fb59efd7d471d82a8b9c55b0cbe421ecb4faf7e8b28337
- Size of remote file:
- 438 MB
- SHA256:
- 9b290ae63821b142f69de4ef124383409ae99f5e557285a2e5d32c8e755e8cac
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