Instructions to use srcocotero/bert-qa-es with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use srcocotero/bert-qa-es with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="srcocotero/bert-qa-es")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("srcocotero/bert-qa-es") model = AutoModelForQuestionAnswering.from_pretrained("srcocotero/bert-qa-es", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 46275a1b671b0c3cf26cce7fd5b21461e6f438744a50e7c185e382332383badd
- Size of remote file:
- 437 MB
- SHA256:
- 1da3f04b505544841dcc2cff76b8f141f7786c8f38ef4bbffc79fc22c3824d27
路
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