Instructions to use suthanhcong/results with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use suthanhcong/results with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="suthanhcong/results")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("suthanhcong/results") model = AutoModelForQuestionAnswering.from_pretrained("suthanhcong/results") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3057bc114cb39fdf0a43d657af9a2058c45bd19401996fbf479c9bf9819f50b1
- Size of remote file:
- 5.05 kB
- SHA256:
- d8d4d9f0a844b6021f773c77e3fc3397391584cc27131718c6bb2e5ccd0ba983
路
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