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:
- 3cd0f6e9792d1f71f431e46a8537c7b4284810902b8340cdaabc30da2e5570f2
- Size of remote file:
- 3.58 kB
- SHA256:
- 4a07368f8e9f3c49ac59ec018d24ac6b252d4e4adfb4d19ac29776412d2525e3
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