Instructions to use cgt/pert-qa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cgt/pert-qa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="cgt/pert-qa")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("cgt/pert-qa") model = AutoModelForQuestionAnswering.from_pretrained("cgt/pert-qa") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 81bc3a3526646599cd51a0892ff016403a465284e283b427908a31731e43acb7
- Size of remote file:
- 1.3 GB
- SHA256:
- abe5aec7c71378d970deedad01be2e6dec39502a477fa4176b39a4ce5a38bd15
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