Instructions to use hf-tiny-model-private/tiny-random-MPNetForQuestionAnswering with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-MPNetForQuestionAnswering with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="hf-tiny-model-private/tiny-random-MPNetForQuestionAnswering")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-MPNetForQuestionAnswering") model = AutoModelForQuestionAnswering.from_pretrained("hf-tiny-model-private/tiny-random-MPNetForQuestionAnswering") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 705a8ecc07a93ddb16c57111c4c843bfa69f73fe04557581af3e13c646e534e9
- Size of remote file:
- 957 kB
- SHA256:
- 389dde52225ecc184dd35cb30660618a0045cc4ec448e20e51826eb408558b3d
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