Instructions to use wskhanh/pert-qa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use wskhanh/pert-qa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="wskhanh/pert-qa")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("wskhanh/pert-qa") model = AutoModelForQuestionAnswering.from_pretrained("wskhanh/pert-qa", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f9d4e440b0b6648d6f46dd2c0d77ae78b31966413fd6f3d69429415d48510ffc
- Size of remote file:
- 3.5 kB
- SHA256:
- 75c610521e9e49b66c05bfc343395aba6a9e391a1341fdea6478dee30b2db311
路
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