Text Classification
Transformers
PyTorch
TensorBoard
Safetensors
English
bert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use JeremiahZ/bert-base-uncased-stsb with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JeremiahZ/bert-base-uncased-stsb with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="JeremiahZ/bert-base-uncased-stsb")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("JeremiahZ/bert-base-uncased-stsb") model = AutoModelForSequenceClassification.from_pretrained("JeremiahZ/bert-base-uncased-stsb") - Notebooks
- Google Colab
- Kaggle
Commit History
Adding `safetensors` variant of this model (#1) 84334fc
update model card README.md 3cc333b
Jeremiah Zhou commited on
End of training a64de90
Jeremiah Zhou commited on
update model card README.md 18c7aff
Jeremiah Zhou commited on
Model save 4e63cd3
Jeremiah Zhou commited on
Training in progress, epoch 3 58b0059
Jeremiah Zhou commited on
Training in progress, epoch 1 1dcb268
Jeremiah Zhou commited on
initial commit ac29321
Jeremiah Zhou commited on