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:
# 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") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e005d58bc0ca218354309f454314906a8fda0ba3ca0a2247bf8a080a9144746f
- Size of remote file:
- 2.33 GB
- SHA256:
- 1d063b4fd641ee6ec91384431623a13a6dfc4130dde71549a6a2ab2fa8e51ef0
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.