Instructions to use aware-ai/longformer-QA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aware-ai/longformer-QA with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="aware-ai/longformer-QA")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("aware-ai/longformer-QA") model = AutoModelForQuestionAnswering.from_pretrained("aware-ai/longformer-QA") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 74ec46c6e83f384f2557c3069b82864d32299356cf54c8a309d76be0a262d560
- Size of remote file:
- 1.18 GB
- SHA256:
- a1bc4743b11ba342d4df28bc93aa1966e96eb28daae4a62df04e07636aca67b1
路
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.