Instructions to use hf-tiny-model-private/tiny-random-XmodForQuestionAnswering 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-XmodForQuestionAnswering 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-XmodForQuestionAnswering")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-XmodForQuestionAnswering") model = AutoModelForQuestionAnswering.from_pretrained("hf-tiny-model-private/tiny-random-XmodForQuestionAnswering") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 804aa61a63aefc6368aa86c27ab7d410ab86e4506cc541a587c8ac63be1070da
- Size of remote file:
- 32.2 MB
- SHA256:
- c6e70109816d4ca4964b63d699d6f2574d7f9f968e10eea079f5cd322bd9367a
路
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