Instructions to use hf-internal-testing/tiny-random-FNetForNextSentencePrediction with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-FNetForNextSentencePrediction with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForNextSentencePrediction tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-FNetForNextSentencePrediction") model = AutoModelForNextSentencePrediction.from_pretrained("hf-internal-testing/tiny-random-FNetForNextSentencePrediction", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ce7febcd62ff798a0636733627e8d5003bc90970e7927b8bfa79fd32f319c1a8
- Size of remote file:
- 4.24 MB
- SHA256:
- 62a2cc321e61825eca6f9403f6ee9575fb415541895a7e1e03c34c6bfc296101
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