Instructions to use Erfan/mT5-base_Farsi_Title_Generator with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Erfan/mT5-base_Farsi_Title_Generator with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Erfan/mT5-base_Farsi_Title_Generator") model = AutoModelForSeq2SeqLM.from_pretrained("Erfan/mT5-base_Farsi_Title_Generator", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Erfan/mT5-base_Farsi_Title_Generator: direct link, hf CLI and curl.
- Browser
- Download file 2.33 GB
-
https://huggingface.co/Erfan/mT5-base_Farsi_Title_Generator/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Erfan/mT5-base_Farsi_Title_Generator/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Erfan/mT5-base_Farsi_Title_Generator/resolve/main/pytorch_model.bin
2.33 GB
- Xet hash:
- e005d58bc0ca218354309f454314906a8fda0ba3ca0a2247bf8a080a9144746f
- Size of remote file:
- 2.33 GB
- SHA256:
- 1d063b4fd641ee6ec91384431623a13a6dfc4130dde71549a6a2ab2fa8e51ef0
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