Instructions to use aaditya/Bluebert_emrqa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aaditya/Bluebert_emrqa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="aaditya/Bluebert_emrqa")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("aaditya/Bluebert_emrqa") model = AutoModelForQuestionAnswering.from_pretrained("aaditya/Bluebert_emrqa", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7c277820bed65294ea2c93b5830cb4d291ff0450887247e99ed36b282eeae22a
- Size of remote file:
- 3.45 kB
- SHA256:
- 0fcbb6e539b5db9527e78c66e1e74c5d458fc773eee009c791cc98527c474e36
路
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.