Instructions to use Shubham09/bartnewlfqa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Shubham09/bartnewlfqa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="Shubham09/bartnewlfqa")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("Shubham09/bartnewlfqa") model = AutoModelForQuestionAnswering.from_pretrained("Shubham09/bartnewlfqa", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3fad183fb306bc7814093774e97fc3613ddfc133fd39d63b6958918291b9c737
- Size of remote file:
- 1.63 GB
- SHA256:
- bb3f89dcdcbd2c1968118106f794fe244460f7c9beef630d5237f319cdfde0d5
路
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