Instructions to use srcocotero/tiny-bert-qa-es with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use srcocotero/tiny-bert-qa-es with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="srcocotero/tiny-bert-qa-es")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("srcocotero/tiny-bert-qa-es") model = AutoModelForQuestionAnswering.from_pretrained("srcocotero/tiny-bert-qa-es") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- eee1b30b455ef9748df056f9f7882b8dbc94a4e94a41fc78fb8d25b7b1320c14
- Size of remote file:
- 3.38 kB
- SHA256:
- d6a7764c920b37cf1d8421c1d711b63d50af1535eceb79c00facdd7339dbfcf0
路
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