Instructions to use hf-tiny-model-private/tiny-random-DistilBertForQuestionAnswering 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-DistilBertForQuestionAnswering 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-DistilBertForQuestionAnswering")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-DistilBertForQuestionAnswering") model = AutoModelForQuestionAnswering.from_pretrained("hf-tiny-model-private/tiny-random-DistilBertForQuestionAnswering") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 07b7e9ffa6bdeef512c94bfd5b9a3ac6fed7a1c99ef8a8996b640be1dbea1e90
- Size of remote file:
- 355 kB
- SHA256:
- aa96086ea0702607946df66c6c8ea5489c21b53507d73d8ed0fde020dd61228f
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