Instructions to use ModelTC/bart-base-squad2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ModelTC/bart-base-squad2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="ModelTC/bart-base-squad2", device_map="auto")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("ModelTC/bart-base-squad2") model = AutoModelForQuestionAnswering.from_pretrained("ModelTC/bart-base-squad2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fff3b777f5a2bcb963618cb622374857ec0b7b66d5755281b570d68fb3a0ab06
- Size of remote file:
- 558 MB
- SHA256:
- 427ec3e8ee14b8a6945970eebd59aef561a990d576c0a7c67f5498871a720531
路
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