Instructions to use howey/bert-base-uncased-sst2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use howey/bert-base-uncased-sst2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="howey/bert-base-uncased-sst2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("howey/bert-base-uncased-sst2") model = AutoModelForSequenceClassification.from_pretrained("howey/bert-base-uncased-sst2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 470e52cacbc9852293157a1f083a27238c7a5bb9b83c518860da02b633a22b4b
- Size of remote file:
- 2.42 kB
- SHA256:
- b2987be78eca33880309cb9273bac03f6cfc5eb4644398f2c3a7f3c38f811126
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