Instructions to use niuca/T5-learning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use niuca/T5-learning with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("niuca/T5-learning") model = AutoModelForSeq2SeqLM.from_pretrained("niuca/T5-learning", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download spiece.model from niuca/T5-learning: direct link, hf CLI and curl.
- Browser
- Download file 795 kB
-
https://huggingface.co/niuca/T5-learning/resolve/main/spiece.model
- Command line
-
hf download hf://niuca/T5-learning/spiece.model
-
curl -L -o spiece.model https://huggingface.co/niuca/T5-learning/resolve/main/spiece.model
795 kB
- Xet hash:
- 3c16bc12b7e83757c14a34b71bc5c107496da9bb4f46f7eb1f9b9faa62ff03e1
- Size of remote file:
- 795 kB
- SHA256:
- e3722a968d6422a0bec4d3cf3a398aa3ff6ccb0dabb02d2f3eeb629b8cb043b6
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