Text Classification
Transformers
PyTorch
English
bert
Eval Results (legacy)
text-embeddings-inference
Instructions to use MattStammers/Statement_Equivalence with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MattStammers/Statement_Equivalence with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="MattStammers/Statement_Equivalence")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("MattStammers/Statement_Equivalence") model = AutoModelForSequenceClassification.from_pretrained("MattStammers/Statement_Equivalence") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1 opened over 1 year ago
by
SFconvertbot