Instructions to use hf-tiny-model-private/tiny-random-MegaForQuestionAnswering 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-MegaForQuestionAnswering 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-MegaForQuestionAnswering")# Load model directly from transformers import AutoModelForQuestionAnswering model = AutoModelForQuestionAnswering.from_pretrained("hf-tiny-model-private/tiny-random-MegaForQuestionAnswering", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bc48ee543e21ae48f042725add16198bcc4778fcc45a778947336ea1e80e3b41
- Size of remote file:
- 382 kB
- SHA256:
- 7a0e706a4fac9c411e15eea4658e6a6f4a00c29ec8eb2dd9c1b20f58eb8359f1
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