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
- Xet hash:
- f89418817103c34d3d54a4fafa4824d2e2734be0e03257eb3b81ce3af241678e
- Size of remote file:
- 17.5 MB
- SHA256:
- 010ada5add71d2b6d28842357a50246580a7660ae81b6df62d68620df7ebd316
路
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