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:
- ab77f136c1f24444ca78d5845d9dea395427c4c23ab7635137f0ef53ef41115d
- Size of remote file:
- 59 MB
- SHA256:
- 9c6d00c9bf4ab53db0e1b7c66033a1282c692a14cc498f01177cbddb54204d7f
路
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