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:
- 65136842a3173bcbe84c38538a0112e4779297659f2f27f25ef3fe8cb5268ab3
- Size of remote file:
- 16.3 MB
- SHA256:
- 08d4ce8b40c2092406659eb2d93e408142e85605d05b449ff58f16f7c719b7f6
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