Instructions to use RinaL/bert-finetuned-squad with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RinaL/bert-finetuned-squad with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="RinaL/bert-finetuned-squad", device_map="auto")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("RinaL/bert-finetuned-squad") model = AutoModelForQuestionAnswering.from_pretrained("RinaL/bert-finetuned-squad", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f79c738019c2a8f56b4afc3ae6408ee9edb775719a27b67b692852ba15680909
- Size of remote file:
- 4.86 kB
- SHA256:
- 6289f2498c2b65101d6df2bf4e8565deb8105eed3549c13f6d0125f43de18aa0
路
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.