初始化项目，由ModelHub XC社区提供模型

Model: LangAGI-Lab/DOCTOR
Source: Original Platform

.gitattributes

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README.md

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+---
+license: apache-2.0
+datasets:
+- DLI-Lab/DONUT
+widget:
+  - text: 'A: Hi, Viggo. How are you doing today?\nB: Hey, Yovani. I’m doing all right. Thanks for asking.\nA: No problem. I saw that you left your coffee mug on the counter this morning. Did you forget to take it with you?\nB: Yeah, I did. Thanks for grabbing it for me.\nA: No problem at all. I know how busy you are and I didn’t want you to have to come back for it later.\nB: You’re a lifesaver, Yovani. Seriously, thank you so much.'
+  - example_title: 'example 1'
+---
+A dialogue commonsense reasoner that generates Chain-of-Thought knowledge in a multi-hop manner given a dialogue history. Our DOCTOR is trained with [DONUT](https://huggingface.co/datasets/DLI-Lab/DONUT) which is also available on huggingface. 
+## Links for Reference
+
+- **Demo:https://dialoguecot.web.app/** 
+- **Repository:https://github.com/kyle8581/DialogueCoT** 
+- **Paper:https://arxiv.org/abs/2310.09343** 
+- **Point of Contact:mapoout@yonsei.ac.kr** 
+
+![](./figure2_overall.png)
+For more details, you can look at our paper [Dialogue Chain-of-Thought Distillation for Commonsense-aware Conversational Agents](https://arxiv.org/abs/2310.09343).
+If you find the following model helpful, please consider citing our paper!
+
+**BibTeX:**
+```bibtex
+@misc{chae2023dialogue,
+      title={Dialogue Chain-of-Thought Distillation for Commonsense-aware Conversational Agents}, 
+      author={Hyungjoo Chae and Yongho Song and Kai Tzu-iunn Ong and Taeyoon Kwon and Minjin Kim and Youngjae Yu and Dongha Lee and Dongyeop Kang and Jinyoung Yeo},
+      year={2023},
+      eprint={2310.09343},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL}
+}
+```

config.json

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+{
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+  "_remove_final_layer_norm": false,
+  "activation_dropout": 0.0,
+  "activation_function": "relu",
+  "architectures": [
+    "OPTForCausalLM"
+  ],
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+  "bos_token_id": 2,
+  "do_layer_norm_before": true,
+  "dropout": 0.1,
+  "enable_bias": true,
+  "eos_token_id": 2,
+  "ffn_dim": 8192,
+  "hidden_size": 2048,
+  "init_std": 0.02,
+  "layer_norm_elementwise_affine": true,
+  "layerdrop": 0.0,
+  "max_position_embeddings": 2048,
+  "model_type": "opt",
+  "num_attention_heads": 32,
+  "num_hidden_layers": 24,
+  "pad_token_id": 1,
+  "prefix": "</s>",
+  "torch_dtype": "float32",
+  "transformers_version": "4.30.0.dev0",
+  "use_cache": false,
+  "vocab_size": 50272,
+  "word_embed_proj_dim": 2048
+}

generation_config.json

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+{
+  "max_new_tokens": 256,
+  "transformers_version": "4.30.0.dev0"
+}

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pytorch_model.bin

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special_tokens_map.json

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+}

tokenizer_config.json

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+{
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+  "add_prefix_space": false,
+  "bos_token": {
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+  "padding_side": "right",
+  "tokenizer_class": "GPT2Tokenizer",
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+    "normalized": true,
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+}

training_args.bin

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