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:
- 028d341462edbf6742a3e25c6124853368e84f757a4cc16e89bb3a62ac8c005a
- Size of remote file:
- 3.58 kB
- SHA256:
- 334a893a6eceb3075e71aac349297db2fb2400ff2984ca6c26302a62090a3fda
路
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