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 pytorch_model.bin from stefan-it/it5-efficient-small-el32: direct link, hf CLI and curl.
- Browser
- Download file 569 MB
-
https://huggingface.co/stefan-it/it5-efficient-small-el32/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://stefan-it/it5-efficient-small-el32/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/stefan-it/it5-efficient-small-el32/resolve/main/pytorch_model.bin
569 MB
- Xet hash:
- e1770b2255e2dae756f4a7b6c80c1caef065223181ce1b7389c36a45f0f93840
- Size of remote file:
- 569 MB
- SHA256:
- 17207cfa4197310019b8a0d286f1cae914abbbd0f0c0e41114e0b56bc56165a3
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