Transformers
PyTorch
Chinese
mt5
text2text-generation
mt5-small
dialog state tracking
conversational system
task-oriented dialog
Eval Results (legacy)
Instructions to use ConvLab/mt5-small-dst-crosswoz with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ConvLab/mt5-small-dst-crosswoz with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("ConvLab/mt5-small-dst-crosswoz") model = AutoModelForSeq2SeqLM.from_pretrained("ConvLab/mt5-small-dst-crosswoz") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f24790f13cb731ae1c3fa31fff0eede8e5d6ff953b1ddfd4fe9cbad922632843
- Size of remote file:
- 1.2 GB
- SHA256:
- 86eb04447e3434fd88e327f93b1cfe3abeefbb74999933622775f961638a655e
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