Instructions to use letrunglinh/qa_pnc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use letrunglinh/qa_pnc with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="letrunglinh/qa_pnc")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("letrunglinh/qa_pnc") model = AutoModelForQuestionAnswering.from_pretrained("letrunglinh/qa_pnc", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3d54cde42002d5471c269ae53912d94b95c6a4c49c87f104aa3a6ad7c9661cca
- Size of remote file:
- 2.24 GB
- SHA256:
- 19be6e4d2f8a31bcf159420fd7af8591df71b3094d60ce5e1b63c504ecc493d4
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