Transformers
PyTorch
Chinese
mt5
text2text-generation
mt5-small
natural language generation
conversational system
task-oriented dialog
Eval Results (legacy)
Instructions to use ConvLab/mt5-small-nlg-all-crosswoz with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ConvLab/mt5-small-nlg-all-crosswoz with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("ConvLab/mt5-small-nlg-all-crosswoz") model = AutoModelForSeq2SeqLM.from_pretrained("ConvLab/mt5-small-nlg-all-crosswoz", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 808349eb481d961411eb4b3f8168835b52f30c1b1d2293b9d7cd152fd1f98e53
- Size of remote file:
- 1.2 GB
- SHA256:
- 42c2d7e1c91da7d5671331463a957ab62a07608a9b745fd11d3328a4321ccc73
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