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:
- 48e78c06d383f4845bed181745197cff5d4affda5bab0b15edb263fd5e73f061
- Size of remote file:
- 938 kB
- SHA256:
- 3a0f995089289538b4b3f56c2af3255bb720bfc8c8bc8be404f729c58ce5d08a
路
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