Text Classification
Transformers
PyTorch
TensorBoard
albert
Generated from Trainer
Eval Results (legacy)
Instructions to use anirudh21/albert-base-v2-finetuned-qnli with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use anirudh21/albert-base-v2-finetuned-qnli with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="anirudh21/albert-base-v2-finetuned-qnli")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("anirudh21/albert-base-v2-finetuned-qnli") model = AutoModelForSequenceClassification.from_pretrained("anirudh21/albert-base-v2-finetuned-qnli") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0045d274e3c956168f4d3796a11428dcba5223119f791a467dc140ffefb77981
- Size of remote file:
- 46.8 MB
- SHA256:
- fa596bb129e6febc452b484a758baf423e2c5ecf74745b19128478bdaf30ec4a
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