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:
- f04eddc81211d19a205368185cca2fe1401a800e7ec00afb0b22797857139a2c
- Size of remote file:
- 1.63 GB
- SHA256:
- 09d7541050745829ecb4d7053afaa90f52999b84fbb4bdc9d273432cb85de761
路
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