Text Classification
Transformers
Safetensors
English
bert
mnli
multinli
natural-language-inference
sequence-classification
Eval Results (legacy)
text-embeddings-inference
Instructions to use Lidor-Mashiach/bert-base-mnli with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Lidor-Mashiach/bert-base-mnli with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Lidor-Mashiach/bert-base-mnli")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Lidor-Mashiach/bert-base-mnli") model = AutoModelForSequenceClassification.from_pretrained("Lidor-Mashiach/bert-base-mnli", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "model": "BERT-base", | |
| "dataset": "MNLI", | |
| "validation_accuracy": 0.839429444727458, | |
| "validation_examples": 9815, | |
| "validation_split": "validation_matched", | |
| "test_accuracy": 0.8444873881204231, | |
| "test_examples": 9832, | |
| "test_split": "validation_mismatched" | |
| } |