Instructions to use hf-internal-testing/tiny-random-longt5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-longt5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-longt5")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-longt5") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-longt5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 54b4d7288c9d68c2cdd2b45479c12d8a3a7b16cd84a95432ee084bff6e1a6e27
- Size of remote file:
- 2.93 MB
- SHA256:
- 68755eddc9f9462799496dd1eb3f239328835345f3c85c283c08ea0530407ac9
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