Instructions to use Erfan/mT5-base_Farsi_Title_Generator_plus 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 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") model = AutoModelForSeq2SeqLM.from_pretrained("Erfan/mT5-base_Farsi_Title_Generator_plus", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from Erfan/mT5-base_Farsi_Title_Generator_plus: direct link, hf CLI and curl.
- Browser
- Download file 16.3 MB
-
https://huggingface.co/Erfan/mT5-base_Farsi_Title_Generator_plus/resolve/main/tokenizer.json
- Command line
-
hf download hf://Erfan/mT5-base_Farsi_Title_Generator_plus/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/Erfan/mT5-base_Farsi_Title_Generator_plus/resolve/main/tokenizer.json
16.3 MB
- Xet hash:
- 153f5eff8511b5f17053182159fc1e03973d4d03b69f8192ce57e7e59c0f2f81
- Size of remote file:
- 16.3 MB
- SHA256:
- 42f010b091679bf059b843dc6b489957b6eae9ce63f866dc5fecb77055f8a581
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