Text Classification
Transformers
PyTorch
TensorBoard
albert
Generated from Trainer
Eval Results (legacy)
Instructions to use anirudh21/albert-base-v2-finetuned-rte with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use anirudh21/albert-base-v2-finetuned-rte with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="anirudh21/albert-base-v2-finetuned-rte")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("anirudh21/albert-base-v2-finetuned-rte") model = AutoModelForSequenceClassification.from_pretrained("anirudh21/albert-base-v2-finetuned-rte") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5b3451333041352c0309a2bc402121541c00a68b9652ba4410886c21855bc509
- Size of remote file:
- 46.8 MB
- SHA256:
- 3ab2a79517a84684b85c9037b93e2c2a7538ee3601e6ebcb7c022c5b7253e5bf
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