Instructions to use hf-internal-testing/tiny-random-FNetForQuestionAnswering with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-FNetForQuestionAnswering 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="hf-internal-testing/tiny-random-FNetForQuestionAnswering")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-FNetForQuestionAnswering") model = AutoModelForQuestionAnswering.from_pretrained("hf-internal-testing/tiny-random-FNetForQuestionAnswering", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from hf-internal-testing/tiny-random-FNetForQuestionAnswering: direct link, hf CLI and curl.
- Browser
- Download file 4.24 MB
-
https://huggingface.co/hf-internal-testing/tiny-random-FNetForQuestionAnswering/resolve/6acfc462747e41a4c15fec0faade3b2af83d42ae/pytorch_model.bin
- Command line
-
hf download hf://hf-internal-testing/tiny-random-FNetForQuestionAnswering@6acfc462747e41a4c15fec0faade3b2af83d42ae/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/hf-internal-testing/tiny-random-FNetForQuestionAnswering/resolve/6acfc462747e41a4c15fec0faade3b2af83d42ae/pytorch_model.bin
4.24 MB
- Xet hash:
- f746c45e560e5b59d904a6762337e7fff0fb9368a515058af5b6243a47e572aa
- Size of remote file:
- 4.24 MB
- SHA256:
- 1fe52e6f41807e30fae64de0f7b696d0370e28b0f28a91220c2c2aa19d5b5559
路
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