Instructions to use madlag/albert-base-v2-squad with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use madlag/albert-base-v2-squad with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="madlag/albert-base-v2-squad")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("madlag/albert-base-v2-squad") model = AutoModelForQuestionAnswering.from_pretrained("madlag/albert-base-v2-squad") - Notebooks
- Google Colab
- Kaggle
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Check out the documentation for more information.
Albert v2 finetuned on SQuAD v1.
Trained using the nn_pruning script, with pruning disabled.
Original results are F1=90.2, EM=83.2, we improved them to:
"exact_match": 83.74645222327341,
"f1": 90.78776054621733
}```
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