Instructions to use hf-tiny-model-private/tiny-random-FNetForNextSentencePrediction 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-FNetForNextSentencePrediction with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForNextSentencePrediction tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-FNetForNextSentencePrediction") model = AutoModelForNextSentencePrediction.from_pretrained("hf-tiny-model-private/tiny-random-FNetForNextSentencePrediction") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b4a23d2a9ec15ceb01343a5aad0258e781180645f615d3a9a66d36bb5da0ab72
- Size of remote file:
- 4.24 MB
- SHA256:
- 574808ea880a4e97bcd5008ed890ee661c53a1142acc17399d05525c8f572053
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