Instructions to use hf-tiny-model-private/tiny-random-LiltForQuestionAnswering 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-LiltForQuestionAnswering 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-LiltForQuestionAnswering")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-LiltForQuestionAnswering") model = AutoModelForQuestionAnswering.from_pretrained("hf-tiny-model-private/tiny-random-LiltForQuestionAnswering") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 700ff16b784abe9ecb091f911f2fe396ebb8637d3904418984936b83b717a48c
- Size of remote file:
- 278 kB
- SHA256:
- 43d77e9895445e3760c934cf94ba7ff07e6eef38a1759ec067640121bc4b91da
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