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:
- 0d302240edfd8834e23e1b8cc02d6e5107b99e8e03355e44b46ad9d40118d85d
- Size of remote file:
- 21 MB
- SHA256:
- 65590b6cd8bbb9d63d75418597e4a278785bf3715041b39d1f2120ecf8120f6c
路
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.