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:
- 549540a7ed23b12cb95fdf7523c58599f3c9abcd0fdb4b1ff59ca1e58270476b
- Size of remote file:
- 32.3 MB
- SHA256:
- 82d77e5e7c9693ce93d09f3c5df24850a6bed767426ece70ede49a9e8b96369d
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