Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use autoevaluate/natural-language-inference with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use autoevaluate/natural-language-inference with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="autoevaluate/natural-language-inference")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("autoevaluate/natural-language-inference") model = AutoModelForSequenceClassification.from_pretrained("autoevaluate/natural-language-inference") - Notebooks
- Google Colab
- Kaggle
Librarian Bot: Add base_model information to model
#10 opened over 2 years ago
by
librarian-bot
Adding `safetensors` variant of this model
#9 opened about 3 years ago
by
SFconvertbot
Add evaluation results on the mrpc config and validation split of glue
#8 opened over 3 years ago
by
lewtun
Add evaluation results on the mrpc config and validation split of glue
#7 opened over 3 years ago
by
lewtun
Add evaluation results on the mrpc config and validation split of glue
#6 opened over 3 years ago
by
lewtun
Add evaluation results on the mrpc config and validation split of glue
#5 opened over 3 years ago
by
lewtun
Add evaluation results on the mrpc config and validation split of glue
#4 opened over 3 years ago
by
lewtun
Add evaluation results on the mrpc config of glue
#3 opened almost 4 years ago
by
abhishek
Add evaluation results on the mrpc config of glue
#1 opened almost 4 years ago
by
abhishek