Instructions to use hf-internal-testing/tiny-random-SplinterForQuestionAnswering with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-SplinterForQuestionAnswering with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="hf-internal-testing/tiny-random-SplinterForQuestionAnswering")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-SplinterForQuestionAnswering") model = AutoModelForQuestionAnswering.from_pretrained("hf-internal-testing/tiny-random-SplinterForQuestionAnswering", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 74d0f690aa10c25c5ce5c800d73f686b43df1922b1410215aa79252bc562183f
- Size of remote file:
- 4.08 MB
- SHA256:
- 301ae48056cff54822a85a7ec40fd62ddd8f164061d53260958426b330eacbce
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