Instructions to use psxjp5/mt5-small_old with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use psxjp5/mt5-small_old with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("psxjp5/mt5-small_old") model = AutoModelForSeq2SeqLM.from_pretrained("psxjp5/mt5-small_old", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from psxjp5/mt5-small_old: direct link, hf CLI and curl.
- Browser
- Download file 1.2 GB
-
https://huggingface.co/psxjp5/mt5-small_old/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://psxjp5/mt5-small_old/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/psxjp5/mt5-small_old/resolve/main/pytorch_model.bin
1.2 GB
- Xet hash:
- 5a6af582101f313e33346524919a664651a598b2eaa3c5fd79216f44140f71d0
- Size of remote file:
- 1.2 GB
- SHA256:
- 206483137ef60db92321d88bb68c139f3f7f14a94b70fb3c978b4f439f9bbe51
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