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
Upload tokenizer_config.json with huggingface_hub
Browse files- tokenizer_config.json +12 -0
tokenizer_config.json
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{
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"additional_special_tokens": null,
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"eos_token": "</s>",
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"extra_ids": 0,
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"name_or_path": "/data/zhuqi/pre-trained-models/mt5-small",
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"pad_token": "<pad>",
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"sp_model_kwargs": {},
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"special_tokens_map_file": "/data/zhuqi/pre-trained-models/mt5-small/special_tokens_map.json",
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"tokenizer_class": "T5Tokenizer",
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"truncation_side": "left",
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"unk_token": "<unk>"
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}
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