Instructions to use hf-tiny-model-private/tiny-random-MegatronBertForQuestionAnswering 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-MegatronBertForQuestionAnswering 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-MegatronBertForQuestionAnswering")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-MegatronBertForQuestionAnswering") model = AutoModelForQuestionAnswering.from_pretrained("hf-tiny-model-private/tiny-random-MegatronBertForQuestionAnswering") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f94cb5bcec59bafc647aab2e19da1b08a4f10be541e4e0a0a00719f86fc723a2
- Size of remote file:
- 872 kB
- SHA256:
- a2ff4703bb8c25b01ae0b1f88dd519477dd187632a347b7e75e140db2f0a604b
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