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 from transformers import pipeline pipe = pipeline("question-answering", model="hf-tiny-model-private/tiny-random-FNetForQuestionAnswering")# 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") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2f433a312e6cf0f6addac2daa6547a634e804e84cc725fecddb9580c8f98fd98
- Size of remote file:
- 4.23 MB
- SHA256:
- 00c898c45db7d891f559be5ccefefc46d46b2eea6a1faeeb537db1987c56e76e
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