Instructions to use ydshieh/tiny-random-LiltForQuestionAnswering with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ydshieh/tiny-random-LiltForQuestionAnswering with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "question-answering" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("question-answering", model="ydshieh/tiny-random-LiltForQuestionAnswering")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("ydshieh/tiny-random-LiltForQuestionAnswering") model = AutoModelForQuestionAnswering.from_pretrained("ydshieh/tiny-random-LiltForQuestionAnswering", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from ydshieh/tiny-random-LiltForQuestionAnswering: direct link, hf CLI and curl.
- Browser
- Download file 293 kB
-
https://huggingface.co/ydshieh/tiny-random-LiltForQuestionAnswering/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://ydshieh/tiny-random-LiltForQuestionAnswering/pytorch_model.bin
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curl -L -o pytorch_model.bin https://huggingface.co/ydshieh/tiny-random-LiltForQuestionAnswering/resolve/main/pytorch_model.bin
293 kB
- Xet hash:
- 3f5be3bac8f7e209c731c0b3779c48efb1f5efcbc92de3afc6063804216ac5d2
- Size of remote file:
- 293 kB
- SHA256:
- d53678f67f9972db5088fa2094906b0504b41919d8d5793a62654f6897bf2e3b
路
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