Instructions to use hf-internal-testing/tiny-random-LongT5Model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-LongT5Model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-LongT5Model")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-LongT5Model") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-LongT5Model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- dc16ba506d418e1c96662587d664858ca58420f57e1244e6777f2b825534adc1
- Size of remote file:
- 4.47 MB
- SHA256:
- d62a1e5b08ca99d3e76f068891dd957b68715060c3fead70d41ab487f7091bdb
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