Instructions to use Shubham09/bart_lfqa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Shubham09/bart_lfqa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="Shubham09/bart_lfqa")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("Shubham09/bart_lfqa") model = AutoModelForQuestionAnswering.from_pretrained("Shubham09/bart_lfqa", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6724c641de8a4256e6596fffe60e46645abfa440e592da4900eed40cf4de8c5d
- Size of remote file:
- 3.58 kB
- SHA256:
- a990de7d886d7803bfd6744c223fa69fdbf59a1ec21fbb28fec70fd090253c00
路
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