Instructions to use ZhiguangHan/mt5-small-task2-dataset3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ZhiguangHan/mt5-small-task2-dataset3 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("ZhiguangHan/mt5-small-task2-dataset3") model = AutoModelForSeq2SeqLM.from_pretrained("ZhiguangHan/mt5-small-task2-dataset3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bcd23c2c66a1cd455f0a193eb48f40ff06ea270d0b4e04772ebfb33731e54e69
- Size of remote file:
- 4.73 kB
- SHA256:
- 4712ed32fdee628025eb2e8801b3ce54ecb94782fb96ad9ba8702740a2a2ee4b
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