Instructions to use ZhiguangHan/mt5-small-task1-dataset4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ZhiguangHan/mt5-small-task1-dataset4 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("ZhiguangHan/mt5-small-task1-dataset4") model = AutoModelForSeq2SeqLM.from_pretrained("ZhiguangHan/mt5-small-task1-dataset4", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4e377b159c66b029439ea5121d840830a3cb2919ceaa16a99a3439141ad979c3
- Size of remote file:
- 4.73 kB
- SHA256:
- 9f486d78656fdf2c7d188ead286e17fb5c9cf9c0be5beb8c82379456af95f58c
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