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Model: microsoft/DialoGPT-small
Source: Original Platform

.gitattributes

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README.md

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+---
+thumbnail: https://huggingface.co/front/thumbnails/dialogpt.png
+tags:
+- conversational
+license: mit
+---
+
+## A State-of-the-Art Large-scale Pretrained Response generation model (DialoGPT)
+
+DialoGPT is a SOTA large-scale pretrained dialogue response generation model for multiturn conversations. 
+The [human evaluation results](https://github.com/dreasysnail/Dialogpt_dev#human-evaluation) indicate that the response generated from DialoGPT is comparable to human response quality under a single-turn conversation Turing test.
+The model is trained on 147M multi-turn dialogue from Reddit discussion thread. 
+
+* Multi-turn generation examples from an interactive environment:
+
+|Role | Response |
+|---------|--------|
+|User | Does money buy happiness? |
+| Bot |  Depends how much money you spend on it .|
+|User | What is the best way to buy happiness ? |
+| Bot | You just have to be a millionaire by your early 20s, then you can be happy . |
+|User |This is so difficult ! |
+| Bot | You have no idea how hard it is to be a millionaire and happy . There is a reason the rich have a lot of money |
+
+Please find the information about preprocessing, training and full details of the DialoGPT in the [original DialoGPT repository](https://github.com/microsoft/DialoGPT)
+
+ArXiv paper: [https://arxiv.org/abs/1911.00536](https://arxiv.org/abs/1911.00536)
+
+### How to use
+
+Now we are ready to try out how the model works as a chatting partner!
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+import torch
+
+
+tokenizer = AutoTokenizer.from_pretrained("microsoft/DialoGPT-small")
+model = AutoModelForCausalLM.from_pretrained("microsoft/DialoGPT-small")
+
+# Let's chat for 5 lines
+for step in range(5):
+	# encode the new user input, add the eos_token and return a tensor in Pytorch
+	new_user_input_ids = tokenizer.encode(input(">> User:") + tokenizer.eos_token, return_tensors='pt')
+
+	# append the new user input tokens to the chat history
+	bot_input_ids = torch.cat([chat_history_ids, new_user_input_ids], dim=-1) if step > 0 else new_user_input_ids
+
+	# generated a response while limiting the total chat history to 1000 tokens, 
+	chat_history_ids = model.generate(bot_input_ids, max_length=1000, pad_token_id=tokenizer.eos_token_id)
+
+	# pretty print last ouput tokens from bot
+	print("DialoGPT: {}".format(tokenizer.decode(chat_history_ids[:, bot_input_ids.shape[-1]:][0], skip_special_tokens=True)))
+```
+
+# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
+Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_microsoft__DialoGPT-small)
+
+| Metric                | Value                     |
+|-----------------------|---------------------------|
+| Avg.                  | 25.02   |
+| ARC (25-shot)         | 25.77          |
+| HellaSwag (10-shot)   | 25.79    |
+| MMLU (5-shot)         | 25.81         |
+| TruthfulQA (0-shot)   | 47.49   |
+| Winogrande (5-shot)   | 50.28   |
+| GSM8K (5-shot)        | 0.0        |
+| DROP (3-shot)         | 0.0         |

config.json

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+{
+  "activation_function": "gelu_new",
+  "architectures": [
+    "GPT2LMHeadModel"
+  ],
+  "attn_pdrop": 0.1,
+  "bos_token_id": 50256,
+  "embd_pdrop": 0.1,
+  "eos_token_id": 50256,
+  "initializer_range": 0.02,
+  "layer_norm_epsilon": 1e-05,
+  "model_type": "gpt2",
+  "n_ctx": 1024,
+  "n_embd": 768,
+  "n_head": 12,
+  "n_layer": 12,
+  "n_positions": 1024,
+  "resid_pdrop": 0.1,
+  "summary_activation": null,
+  "summary_first_dropout": 0.1,
+  "summary_proj_to_labels": true,
+  "summary_type": "cls_index",
+  "summary_use_proj": true,
+  "task_specific_params": {
+    "conversational": {
+      "max_length": 1000
+    }
+  },
+  "vocab_size": 50257
+}

configuration.json

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+{"framework": "pytorch", "task": "text-generation", "allow_remote": true}

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generation_config.json

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+  "eos_token_id": 50256,
+  "transformers_version": "4.27.0.dev0"
+}

generation_config_for_conversational.json

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tokenizer_config.json

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+{
+  "add_bos_token": false,
+  "add_prefix_space": false,
+  "added_tokens_decoder": {
+    "50256": {
+      "content": "<|endoftext|>",
+      "lstrip": false,
+      "normalized": true,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
+  "bos_token": "<|endoftext|>",
+  "chat_template": "{% for message in messages %}{{ message.content }}{{ eos_token }}{% endfor %}",
+  "clean_up_tokenization_spaces": true,
+  "eos_token": "<|endoftext|>",
+  "errors": "replace",
+  "model_max_length": 1024,
+  "pad_token": null,
+  "tokenizer_class": "GPT2Tokenizer",
+  "unk_token": "<|endoftext|>"
+}