Instructions to use stefan-it/it5-efficient-small-el32 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use stefan-it/it5-efficient-small-el32 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("stefan-it/it5-efficient-small-el32") model = AutoModelForSeq2SeqLM.from_pretrained("stefan-it/it5-efficient-small-el32", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from stefan-it/it5-efficient-small-el32: direct link, hf CLI and curl.
- Browser
- Download file 2.45 MB
-
https://huggingface.co/stefan-it/it5-efficient-small-el32/resolve/main/tokenizer.json
- Command line
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hf download hf://stefan-it/it5-efficient-small-el32/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/stefan-it/it5-efficient-small-el32/resolve/main/tokenizer.json
2.45 MB
File too large to display, you can check the raw version instead.