Instructions to use krishanmittal018/qa_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use krishanmittal018/qa_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="krishanmittal018/qa_model")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("krishanmittal018/qa_model") model = AutoModelForQuestionAnswering.from_pretrained("krishanmittal018/qa_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 93b5abbebbf65d65d76f3791dd068361ccaa1ae1c7fdab95a376ccf17cfc4bdf
- Size of remote file:
- 5.71 kB
- SHA256:
- 24cfbac4f77f3343cea637be111c7f8708fb5a9289934e79b2c772a0f4d84b04
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