Instructions to use tharindu/mt5_cctk with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tharindu/mt5_cctk with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("tharindu/mt5_cctk") model = AutoModelForSeq2SeqLM.from_pretrained("tharindu/mt5_cctk", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from tharindu/mt5_cctk: direct link, hf CLI and curl.
- Browser
- Download file 2.33 GB
-
https://huggingface.co/tharindu/mt5_cctk/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://tharindu/mt5_cctk/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/tharindu/mt5_cctk/resolve/main/pytorch_model.bin
2.33 GB
- Xet hash:
- 1900d81b8db56fa5212937542adc07b190317145c0d157bbd05b2c6b22b6efef
- Size of remote file:
- 2.33 GB
- SHA256:
- ddbd8c26fc6b63128bb9a5bc7cdd1cc838ba0b03e7f9da235eaa82b8cb6b1cc8
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