Instructions to use practice-ac/training_question_answer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use practice-ac/training_question_answer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="practice-ac/training_question_answer")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("practice-ac/training_question_answer") model = AutoModelForQuestionAnswering.from_pretrained("practice-ac/training_question_answer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 688cca41f61416b9e71be0c515a82b18ab3a28ee42541eb5c05fc40ca1d02184
- Size of remote file:
- 498 MB
- SHA256:
- cce3eef239c73878b350bb4da9daf0539fb71263ebf07ab25b917152932f3fc3
路
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