Instructions to use SKaup/t5_small_optimized_secured with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SKaup/t5_small_optimized_secured with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("SKaup/t5_small_optimized_secured") model = AutoModelForSeq2SeqLM.from_pretrained("SKaup/t5_small_optimized_secured", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from SKaup/t5_small_optimized_secured: direct link, hf CLI and curl.
- Browser
- Download file 242 MB
-
https://huggingface.co/SKaup/t5_small_optimized_secured/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://SKaup/t5_small_optimized_secured/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/SKaup/t5_small_optimized_secured/resolve/main/pytorch_model.bin
242 MB
- Xet hash:
- e0743ace844e2500a197a7831451b1d7079e42128628ad3e0082633c16cb20cd
- Size of remote file:
- 242 MB
- SHA256:
- 2e551246c2bfb72e11cfaafa6ab9116fda147b6d76d2920cecdd53558eaad8b7
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