Instructions to use srcocotero/tiny-bert-qa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use srcocotero/tiny-bert-qa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="srcocotero/tiny-bert-qa")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("srcocotero/tiny-bert-qa") model = AutoModelForQuestionAnswering.from_pretrained("srcocotero/tiny-bert-qa") - Notebooks
- Google Colab
- Kaggle
Librarian Bot: Add base_model information to model
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by librarian-bot - opened
README.md
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- generated_from_trainer
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datasets:
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- squad
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model-index:
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- name: mini_model
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results: []
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- generated_from_trainer
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datasets:
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- squad
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base_model: nreimers/BERT-Tiny_L-2_H-128_A-2
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model-index:
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- name: mini_model
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results: []
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