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:
- 2e85b266d33e9326b5a2ad2f010223225ac7105e9aac29eb8d0d9e1292c13fe6
- Size of remote file:
- 16.3 MB
- SHA256:
- 93c3578052e1605d8332eb961bc08d72e246071974e4cc54aa6991826b802aa5
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