---
title: TransferTOD-7B
canonical_url: "https://www.modelscope.cn/models/Mee1ong/TransferTOD-7B"
md_url: "https://www.modelscope.cn/models/Mee1ong/TransferTOD-7B.md"
repository: Mee1ong/TransferTOD-7B
last_updated: 2025-01-26
pipeline_tag: task-oriented-conversation
tasks:
  - task-oriented-conversation
model_type:
  - baichuan
architectures:
  - BaichuanForCausalLM
parameters: 7.5B
tensor_type:
  - BF16
library_name:
  - safetensors
inference_backends:
  - "deploy_task text/emb"
  - "lmdeploy 0.9.1"
  - "lmdeploy_turbomind 0.9.1"
  - "sglang 0.5.2"
  - "vllm 0.9.2"
downloads: 145
stars: 0
---

# TransferTOD-7B

> TransferTOD-7B - Mee1ong 在 ModelScope 开源的模型。TransferTOD The model repository of paper "TransferTOD: A Generalizable Chinese Multi-Domain Task-Oriented Dialogue System with Transfer Capabilities"

Mee1ong/TransferTOD-7B 是 ModelScope 魔搭社区上的 7.5B 参数task-oriented-conversation模型，可用 deploy_task text/emb、lmdeploy 0.9.1、lmdeploy_turbomind 0.9.1 部署。

- **Repository**: Mee1ong/TransferTOD-7B
- **Tasks**: task-oriented-conversation
- **Parameters**: 7.5B
- **Inference backends**: deploy_task text/emb, lmdeploy 0.9.1, lmdeploy_turbomind 0.9.1, sglang 0.5.2, vllm 0.9.2
- **Downloads**: 145
- **Stars**: 0
- **Last updated**: 2025-01-26

Source: https://www.modelscope.cn/models/Mee1ong/TransferTOD-7B

---

# TransferTOD
The model repository of paper "TransferTOD: A Generalizable Chinese Multi-Domain Task-Oriented Dialogue System with Transfer Capabilities"

All the code and data can be found in https://github.com/KongLongGeFDU/TransferTOD

Paper: https://aclanthology.org/2024.emnlp-main.710.pdf

## Data Info
Overall statistics of TransferTOD dataset are as follows:
| | Train | ID Test | OOD Test |
| --- | --- | --- | --- |
| #Domain | 27 | 27 | 3 |
| #Slot | 188 | 188 | 27 |
| #Dialogue | 4320 | 540 | 600 |
| #Turns | 28680 | 3585 | 3700 |
| #Slots/Dialogue | 10.3 | 10.3 | 9.7 |
| #Tokens/Turn | 66.4 | 66.4 | 76.8 |
> ID Test means In-Domain test and OOD Test means Out-of-Domain test. The domains of the test set are Water-Delivery, Sanitation, and Courier.

## Guide
All the data used in two-staged finetuning and the raw data of TransferTOD is included in directory `./data`. For each version, `train.json` is a mixed data of `train_slot.json` and equivalent amounts of `./data/raw_data/belle_data/belle_filtered_950k_train.jsonl`

For full fine-tuning, run `./fine_tune/scripts/finetune_full.sh`, while for lora fine-tuning, run `./fine_tune/scripts/finetune_lora.sh`.

For inference and evaluation with the TransferTOD test set, run `./inference/inference_and_eval.sh`.

## Citation
If you find this project useful in your research, please cite:
```
@inproceedings{DBLP:conf/emnlp/ZhangHWLZDSDZYZ24,
  author       = {Ming Zhang and
                  Caishuang Huang and
                  Yilong Wu and
                  Shichun Liu and
                  Huiyuan Zheng and
                  Yurui Dong and
                  Yujiong Shen and
                  Shihan Dou and
                  Jun Zhao and
                  Junjie Ye and
                  Qi Zhang and
                  Tao Gui and
                  Xuanjing Huang},
  editor       = {Yaser Al{-}Onaizan and
                  Mohit Bansal and
                  Yun{-}Nung Chen},
  title        = {TransferTOD: {A} Generalizable Chinese Multi-Domain Task-Oriented
                  Dialogue System with Transfer Capabilities},
  booktitle    = {Proceedings of the 2024 Conference on Empirical Methods in Natural
                  Language Processing, {EMNLP} 2024, Miami, FL, USA, November 12-16,
                  2024},
  pages        = {12750--12771},
  publisher    = {Association for Computational Linguistics},
  year         = {2024},
  url          = {https://aclanthology.org/2024.emnlp-main.710},
  timestamp    = {Thu, 14 Nov 2024 17:20:55 +0100},
  biburl       = {https://dblp.org/rec/conf/emnlp/ZhangHWLZDSDZYZ24.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}
```

Contact Us:
mingzhang23@m.fudan.edu.cn