Instructions to use srcocotero/mini-bert-qa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use srcocotero/mini-bert-qa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="srcocotero/mini-bert-qa", device_map="auto")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("srcocotero/mini-bert-qa") model = AutoModelForQuestionAnswering.from_pretrained("srcocotero/mini-bert-qa", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c080db641358f2480a58521cafb2b65876bc4aaf1eb6acbdc5ebb358937164df
- Size of remote file:
- 3.38 kB
- SHA256:
- a824e970350fd15fc5ce27dd02e9c726b5638da986a3ad4b66dec819af8cc00b
路
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