Text Classification
Transformers
PyTorch
roberta
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use k4black/textattack-roberta-base-MNLI-e-snli-classification-nli-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use k4black/textattack-roberta-base-MNLI-e-snli-classification-nli-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="k4black/textattack-roberta-base-MNLI-e-snli-classification-nli-base")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("k4black/textattack-roberta-base-MNLI-e-snli-classification-nli-base") model = AutoModelForSequenceClassification.from_pretrained("k4black/textattack-roberta-base-MNLI-e-snli-classification-nli-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
update model card README.md
5040fba -
Model save
aaf3c61 -
Training in progress, step 8800
c20ed3b -
Training in progress, step 7200
00e86fc -
Training in progress, step 5200
094114f -
Training in progress, step 3600
0ebe925 -
Training in progress, step 2000
c984880 -
Training in progress, step 400
4babf2f -
initial commit
4887899