Instructions to use z-uo/roberta-qasper with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use z-uo/roberta-qasper with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="z-uo/roberta-qasper")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("z-uo/roberta-qasper") model = AutoModelForQuestionAnswering.from_pretrained("z-uo/roberta-qasper", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 56cf80386de83c9dcf6328aabb9df8bf2eba4d44498e04b4f57bd38f3b3cbbf4
- Size of remote file:
- 3.06 kB
- SHA256:
- 44dca61e73a457780e3093cd6a96cc4872e7c30841fceecc132da6d0ce08dc8f
路
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