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Model: g34634/qwen2.5-3b-memory-summary-v1 Source: Original Platform
2026-06-13 15:50:18 +08:00
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--- a/README.md
+++ b/README.md
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+---
+language:
+- en
+- ko
+license: apache-2.0
+base_model: Qwen/Qwen2.5-3B-Instruct
+tags:
+- memory
+- multi-turn
+- dialogue
+- json-generation
+- lora
+- sft
+pipeline_tag: text-generation
+---
+
+# Qwen2.5-3B Memory State Generator
+
+[Qwen2.5-3B-Instruct](https://huggingface.co/Qwen/Qwen2.5-3B-Instruct)를 멀티턴 대화에서 구조화된 메모리 상태를 추출하도록 파인튜닝한 모델입니다.
+
+멀티턴 대화 파이프라인에서 라우팅 및 검색 전에 가장 먼저 실행되며, 이후 컴포넌트(Router, RAG, LLM)가 활용할 수 있는 `memory_state` JSON을 생성합니다.
+
+```
+사용자 입력 → [Memory State Generator] → Router → LLM/VLM
+```
+
+---
+
+## 모델 설명
+
+| | |
+|---|---|
+| **베이스 모델** | Qwen/Qwen2.5-3B-Instruct |
+| **파인튜닝 방식** | SFT + LoRA |
+| **학습 데이터** | DialogSum + QMSum |
+| **최대 시퀀스 길이** | 512 |
+| **LoRA rank** | 16 |
+| **GPU** | NVIDIA A100 40GB |
+| **Epoch** | 3 |
+| **최종 Validation Loss** | 0.693 |
+
+---
+
+## 출력 형식
+
+대화를 입력하면 아래 형식의 JSON을 출력합니다.
+
+```json
+{
+  "memory_state": {
+    "key_facts": ["사실1", "사실2"],
+    "unresolved_refs": ["불명확한 지시어나 대명사"],
+    "topic": "대화의 주제",
+    "turn_count": 5
+  },
+  "memory_summary": "지금까지의 대화를 한 문장으로 요약한 내용"
+}
+```
+
+---
+
+## 사용법
+
+```python
+from transformers import AutoTokenizer, AutoModelForCausalLM
+import torch
+import json
+
+model_id = "your-username/qwen2.5-3b-memory-summary-v1"
+
+tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
+model = AutoModelForCausalLM.from_pretrained(
+    model_id,
+    torch_dtype=torch.bfloat16,
+    device_map="auto",
+    trust_remote_code=True
+)
+
+SYSTEM_PROMPT = """You are a Memory State Generator in a multi-turn dialogue system.
+Given a conversation, extract and output a structured memory state as JSON.
+
+Output format (strictly follow this):
+{
+  "memory_state": {
+    "key_facts": ["fact1", "fact2"],
+    "unresolved_refs": ["any unclear references or pronouns"],
+    "topic": "main topic of the conversation",
+    "turn_count": <number of turns>
+  },
+  "memory_summary": "One concise sentence summarizing the conversation so far."
+}
+
+Output only valid JSON. No explanation, no markdown."""
+
+dialogue = """
+A: RAG 파이프라인 구현 완료했어요.
+B: 모델은 어떤 걸 쓰기로 했어요?
+A: Qwen2.5-3B-Instruct로 결정했어요. LoRA로 파인튜닝할 예정입니다.
+"""
+
+messages = [
+    {"role": "system", "content": SYSTEM_PROMPT},
+    {"role": "user", "content": f"Conversation:\n{dialogue}"}
+]
+
+input_text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
+inputs = tokenizer(input_text, return_tensors="pt").to(model.device)
+
+with torch.no_grad():
+    outputs = model.generate(
+        **inputs,
+        max_new_tokens=512,
+        temperature=0.1,
+        do_sample=True,
+        pad_token_id=tokenizer.eos_token_id
+    )
+
+response = tokenizer.decode(outputs[0][inputs["input_ids"].shape[1]:], skip_special_tokens=True)
+parsed = json.loads(response)
+print(json.dumps(parsed, indent=2, ensure_ascii=False))
+```
+
+---
+
+## 학습 정보
+
+### 데이터
+
+| 데이터셋 | 크기 | 설명 |
+|---|---|---|
+| [DialogSum](https://huggingface.co/datasets/knkarthick/dialogsum) | 13,031개 | 일상 대화 + 사람이 작성한 요약문 |
+| [QMSum](https://huggingface.co/datasets/pszemraj/qmsum-cleaned) | 686개 | 회의록 + query 기반 요약 쌍 |
+
+두 데이터셋 모두 `memory_state JSON` 형식으로 변환하여 SFT 학습에 사용했습니다.
+
+### 학습 설정
+
+```python
+LoraConfig(
+    r=16,
+    lora_alpha=32,
+    lora_dropout=0.05,
+    target_modules=["q_proj", "k_proj", "v_proj", "o_proj",
+                    "gate_proj", "up_proj", "down_proj"],
+)
+
+SFTConfig(
+    num_train_epochs=3,
+    per_device_train_batch_size=1,
+    gradient_accumulation_steps=16,
+    learning_rate=2e-4,
+    lr_scheduler_type="cosine",
+    max_seq_length=512,
+    bf16=True,
+)
+```
+
+### 학습 Loss
+
+| Step | Training Loss | Validation Loss |
+|---|---|---|
+| 100 | 14.578 | 0.896 |
+| 500 | 12.919 | 0.804 |
+| 1000 | 11.361 | 0.734 |
+| 1500 | 10.437 | 0.694 |
+| 2000 | 9.783 | 0.694 |
+| 2400 | 9.635 | 0.693 |
+
+---
+
+## 한계점
+
+- 대화 형식에 따라 `turn_count` 추출이 부정확할 수 있습니다
+- `key_facts`가 구체적인 사실 추출보다 추상적인 요약에 가깝게 나오는 경우가 있습니다 — synthetic 데이터 추가 학습으로 개선 예정입니다
+- 짧은~중간 길이 대화에 최적화되어 있습니다 (최대 512 토큰)
+
+---
+
+## 라이선스
+
+Apache 2.0
--- a/chat_template.jinja
+++ b/chat_template.jinja
@@ -0,0 +1,54 @@
+{%- if tools %}
+    {{- '<|im_start|>system\n' }}
+    {%- if messages[0]['role'] == 'system' %}
+        {{- messages[0]['content'] }}
+    {%- else %}
+        {{- 'You are Qwen, created by Alibaba Cloud. You are a helpful assistant.' }}
+    {%- endif %}
+    {{- "\n\n# Tools\n\nYou may call one or more functions to assist with the user query.\n\nYou are provided with function signatures within <tools></tools> XML tags:\n<tools>" }}
+    {%- for tool in tools %}
+        {{- "\n" }}
+        {{- tool | tojson }}
+    {%- endfor %}
+    {{- "\n</tools>\n\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\n<tool_call>\n{\"name\": <function-name>, \"arguments\": <args-json-object>}\n</tool_call><|im_end|>\n" }}
+{%- else %}
+    {%- if messages[0]['role'] == 'system' %}
+        {{- '<|im_start|>system\n' + messages[0]['content'] + '<|im_end|>\n' }}
+    {%- else %}
+        {{- '<|im_start|>system\nYou are Qwen, created by Alibaba Cloud. You are a helpful assistant.<|im_end|>\n' }}
+    {%- endif %}
+{%- endif %}
+{%- for message in messages %}
+    {%- if (message.role == "user") or (message.role == "system" and not loop.first) or (message.role == "assistant" and not message.tool_calls) %}
+        {{- '<|im_start|>' + message.role + '\n' + message.content + '<|im_end|>' + '\n' }}
+    {%- elif message.role == "assistant" %}
+        {{- '<|im_start|>' + message.role }}
+        {%- if message.content %}
+            {{- '\n' + message.content }}
+        {%- endif %}
+        {%- for tool_call in message.tool_calls %}
+            {%- if tool_call.function is defined %}
+                {%- set tool_call = tool_call.function %}
+            {%- endif %}
+            {{- '\n<tool_call>\n{"name": "' }}
+            {{- tool_call.name }}
+            {{- '", "arguments": ' }}
+            {{- tool_call.arguments | tojson }}
+            {{- '}\n</tool_call>' }}
+        {%- endfor %}
+        {{- '<|im_end|>\n' }}
+    {%- elif message.role == "tool" %}
+        {%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != "tool") %}
+            {{- '<|im_start|>user' }}
+        {%- endif %}
+        {{- '\n<tool_response>\n' }}
+        {{- message.content }}
+        {{- '\n</tool_response>' }}
+        {%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
+            {{- '<|im_end|>\n' }}
+        {%- endif %}
+    {%- endif %}
+{%- endfor %}
+{%- if add_generation_prompt %}
+    {{- '<|im_start|>assistant\n' }}
+{%- endif %}
--- a/config.json
+++ b/config.json
@@ -0,0 +1,69 @@
+{
+  "architectures": [
+    "Qwen2ForCausalLM"
+  ],
+  "attention_dropout": 0.0,
+  "bos_token_id": 151643,
+  "dtype": "bfloat16",
+  "eos_token_id": 151645,
+  "hidden_act": "silu",
+  "hidden_size": 2048,
+  "initializer_range": 0.02,
+  "intermediate_size": 11008,
+  "layer_types": [
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention"
+  ],
+  "max_position_embeddings": 32768,
+  "max_window_layers": 70,
+  "model_type": "qwen2",
+  "num_attention_heads": 16,
+  "num_hidden_layers": 36,
+  "num_key_value_heads": 2,
+  "pad_token_id": null,
+  "rms_norm_eps": 1e-06,
+  "rope_parameters": {
+    "rope_theta": 1000000.0,
+    "rope_type": "default"
+  },
+  "sliding_window": null,
+  "tie_word_embeddings": true,
+  "transformers_version": "5.0.0",
+  "use_cache": true,
+  "use_sliding_window": false,
+  "vocab_size": 151936
+}
--- a/generation_config.json
+++ b/generation_config.json
@@ -0,0 +1,14 @@
+{
+  "bos_token_id": 151643,
+  "do_sample": true,
+  "eos_token_id": [
+    151645,
+    151643
+  ],
+  "pad_token_id": 151643,
+  "repetition_penalty": 1.05,
+  "temperature": 0.7,
+  "top_k": 20,
+  "top_p": 0.8,
+  "transformers_version": "5.0.0"
+}
--- a/model.safetensors
+++ b/model.safetensors
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:1d36d214a64b5d7188377c54ded87a1c61a7c2fe49050a4119ba2573bd9b65a3
+size 6171927112
--- a/tokenizer.json
+++ b/tokenizer.json
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:3fd169731d2cbde95e10bf356d66d5997fd885dd8dbb6fb4684da3f23b2585d8
+size 11421892
--- a/tokenizer_config.json
+++ b/tokenizer_config.json
@@ -0,0 +1,30 @@
+{
+  "add_prefix_space": false,
+  "backend": "tokenizers",
+  "bos_token": null,
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "<|im_end|>",
+  "errors": "replace",
+  "extra_special_tokens": [
+    "<|im_start|>",
+    "<|im_end|>",
+    "<|object_ref_start|>",
+    "<|object_ref_end|>",
+    "<|box_start|>",
+    "<|box_end|>",
+    "<|quad_start|>",
+    "<|quad_end|>",
+    "<|vision_start|>",
+    "<|vision_end|>",
+    "<|vision_pad|>",
+    "<|image_pad|>",
+    "<|video_pad|>"
+  ],
+  "is_local": true,
+  "model_max_length": 131072,
+  "model_specific_special_tokens": {},
+  "pad_token": "<|im_end|>",
+  "split_special_tokens": false,
+  "tokenizer_class": "Qwen2Tokenizer",
+  "unk_token": null
+}