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:
- 6319c29ecff753b3f283b19375a0202fe25bd3d5c2e5c04b957a9986449525cb
- Size of remote file:
- 433 MB
- SHA256:
- 1e8b011f1acaf5e32d4ca8ca509a9d7152f36489c0e602d3d38992213eaabeec
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