Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
text-embeddings-inference
Instructions to use doyoungkim/bert-base-uncased-finetuned-sst2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use doyoungkim/bert-base-uncased-finetuned-sst2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="doyoungkim/bert-base-uncased-finetuned-sst2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("doyoungkim/bert-base-uncased-finetuned-sst2") model = AutoModelForSequenceClassification.from_pretrained("doyoungkim/bert-base-uncased-finetuned-sst2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cc1c6cd14803072434b4be4c85205abd1da0f6d27680e33c1c6b4870f65384e6
- Size of remote file:
- 438 MB
- SHA256:
- 08529ab64918137e60028b1db6d71a974e89768657a53720df6dba21499433e6
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