Instructions to use psxjp5/mt5-small_new with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use psxjp5/mt5-small_new with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("psxjp5/mt5-small_new") model = AutoModelForSeq2SeqLM.from_pretrained("psxjp5/mt5-small_new", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from psxjp5/mt5-small_new: direct link, hf CLI and curl.
- Browser
- Download file 1.2 GB
-
https://huggingface.co/psxjp5/mt5-small_new/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://psxjp5/mt5-small_new/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/psxjp5/mt5-small_new/resolve/main/pytorch_model.bin
1.2 GB
- Xet hash:
- 9ba61253c6681394e6bea1a61199eb5ac709dcc4ceb76fe59117c8fb937e47ef
- Size of remote file:
- 1.2 GB
- SHA256:
- d08f55c0cbc4de071ff338819e980a10b94187c421914a029ebb2bdf1b73a313
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