Instructions to use pere/tt5x-3B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pere/tt5x-3B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="pere/tt5x-3B")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("pere/tt5x-3B") model = AutoModel.from_pretrained("pere/tt5x-3B") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 095da9070894e83cbd46f98be0ec92c1f8e9d77ee16bc06b2c43b66e6698a9af
- Size of remote file:
- 11.4 GB
- SHA256:
- 3a7949b5361e2bf30fb803df632c7b39daf5184e7ab620d0df1cd2fce8fc5198
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