Instructions to use Erfan/mT5-base_Farsi_Title_Generator_plus_dec21 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_plus_dec21 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_plus_dec21") model = AutoModelForSeq2SeqLM.from_pretrained("Erfan/mT5-base_Farsi_Title_Generator_plus_dec21", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Erfan/mT5-base_Farsi_Title_Generator_plus_dec21: direct link, hf CLI and curl.
- Browser
- Download file 2.33 GB
-
https://huggingface.co/Erfan/mT5-base_Farsi_Title_Generator_plus_dec21/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Erfan/mT5-base_Farsi_Title_Generator_plus_dec21/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Erfan/mT5-base_Farsi_Title_Generator_plus_dec21/resolve/main/pytorch_model.bin
2.33 GB
- Xet hash:
- 204cd196c3fa73a53fbf390a127ad2c7b7aa10455cab2c88b179c0717a0bc014
- Size of remote file:
- 2.33 GB
- SHA256:
- 6caaa9b09faa3c581cbee537821d8f5d64309af5a92533690577ee9d41f7464d
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