Instructions to use remunds/MiniLM_NaturalQuestions with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use remunds/MiniLM_NaturalQuestions with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="remunds/MiniLM_NaturalQuestions")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("remunds/MiniLM_NaturalQuestions") model = AutoModelForQuestionAnswering.from_pretrained("remunds/MiniLM_NaturalQuestions") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 25897bc6973540331413e158651cf3a9a9d3c61a9a247830e3951ecc33b7fe2d
- Size of remote file:
- 133 MB
- SHA256:
- e2ceb5a336ceadedb590eedba2ad211f60ed67e21fd04cdca4f50ca492654ef1
路
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