Instructions to use Shubham09/BART with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Shubham09/BART with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="Shubham09/BART")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("Shubham09/BART") model = AutoModelForQuestionAnswering.from_pretrained("Shubham09/BART", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 43d0494f4c93dcc09554bfa05a1b5fb209b27c0509d08e94c5eccb3e21b7d9bb
- Size of remote file:
- 3.58 kB
- SHA256:
- f21b644a01701c46940d2bdcc0249db10aafd22f04809b2dbc9f6914a27bafa4
路
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