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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7cb159b3fdbb89625297330c32741bf7434df7d0e42c569f94c3e61585170a11
- Size of remote file:
- 50.2 MB
- SHA256:
- 9a081688d8b7c376f51de99d17659f23ae18ec20133d31f76aaf5335bd1217c9
路
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