Instructions to use hf-tiny-model-private/tiny-random-FNetForQuestionAnswering 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-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-tiny-model-private/tiny-random-FNetForQuestionAnswering")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-FNetForQuestionAnswering") model = AutoModelForQuestionAnswering.from_pretrained("hf-tiny-model-private/tiny-random-FNetForQuestionAnswering", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from hf-tiny-model-private/tiny-random-FNetForQuestionAnswering: direct link, hf CLI and curl.
- Browser
- Download file 4.24 MB
-
https://huggingface.co/hf-tiny-model-private/tiny-random-FNetForQuestionAnswering/resolve/f9854fd76fbc4f522c51d3099bbf2ea9475148e6/pytorch_model.bin
- Command line
-
hf download hf://hf-tiny-model-private/tiny-random-FNetForQuestionAnswering@f9854fd76fbc4f522c51d3099bbf2ea9475148e6/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/hf-tiny-model-private/tiny-random-FNetForQuestionAnswering/resolve/f9854fd76fbc4f522c51d3099bbf2ea9475148e6/pytorch_model.bin
4.24 MB
- Xet hash:
- 7956a61227f650654071906a5a754b91590cc999b3327b9a6503ccf15f3e1128
- Size of remote file:
- 4.24 MB
- SHA256:
- b4f816713d836e2c692adad9475966f1c72b343895ede27474285d27c9e702ba
路
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