Instructions to use tanmeh/qa_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tanmeh/qa_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="tanmeh/qa_model")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("tanmeh/qa_model") model = AutoModelForQuestionAnswering.from_pretrained("tanmeh/qa_model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c626dd2b7fbd622a5b77eeb216e83ada8da4d8b7e86f1cf95d27fe6f1ea00b92
- Size of remote file:
- 4.66 kB
- SHA256:
- 193e8aa166dec9b6768f0f39331a669621185231521386dd9196120d9761e86e
路
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