Text Classification
Transformers
PyTorch
English
bert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use Cheng98/bert-base-sst2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Cheng98/bert-base-sst2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Cheng98/bert-base-sst2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Cheng98/bert-base-sst2") model = AutoModelForSequenceClassification.from_pretrained("Cheng98/bert-base-sst2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- dd1d1e21f33fb4b14945b62ce368c8a0d206a71399b75fd8e503b532e3b597d6
- Size of remote file:
- 3.96 kB
- SHA256:
- 73bfdfe546beaea5baeefff41cfa8179e7587f050d5888877918bbfe68c58521
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