Instructions to use chandra1976/simple_qa_model_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use chandra1976/simple_qa_model_2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="chandra1976/simple_qa_model_2")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("chandra1976/simple_qa_model_2") model = AutoModelForQuestionAnswering.from_pretrained("chandra1976/simple_qa_model_2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d1f3c07644873bb1726a8fb2f5eb65a8ca5b7bc635cc9fb97f59788473a9202a
- Size of remote file:
- 5.84 kB
- SHA256:
- b28465de192c61dead54adbe6599a299ca5c5d1201323244c25c8e18f84f6ae7
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