upload v0.21 source-screen scitech-mrc-300 merged model

LICENSE

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+Copyright (c) 2025 SK Telecom Co., Ltd. All rights reserved.
+
+Unless otherwise stated, all files in this repository (including modified model weights 
+and tokenizer files) are distributed under the terms of the Apache License, Version 2.0 
+(the "License"). You may obtain a copy of the License at:
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software distributed under 
+the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF 
+ANY KIND, either express or implied. See the License for the specific language governing 
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README.md

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+---
+base_model: skt/A.X-3.1-Light
+library_name: transformers
+language:
+- ko
+license: apache-2.0
+pipeline_tag: text-generation
+tags:
+- korean
+- sft
+- lora-merged
+- safetensors
+- k-ai-leaderboard
+- source-screening
+---
+
+# AX-3.1-Light-sft_v0_21_source_screen_scitech_mrc_300
+
+This is a standalone BF16 model obtained by fine-tuning
+[skt/A.X-3.1-Light](https://huggingface.co/skt/A.X-3.1-Light) with a LoRA
+adapter and merging the adapter into the base weights. It is intended for
+Korean-language research and controlled evaluation. The repository contains
+no benchmark data, benchmark answers, training logs, or access credentials.
+
+## Model Details
+
+- Base model: skt/A.X-3.1-Light
+- Base revision used for training and merge: 9b41bb2406472634d8812c0b8931fa40fa9a6c3a
+- Architecture: unchanged from the base model
+- Weight format: BF16 safetensors
+- Chat template: official A.X tokenizer chat template
+- Custom Python model code: none
+- Submission form: merged full model; no separate adapter is required
+- Experiment condition: A v0.21-equivalent source-screening arm replacing 300 rows with technical-science machine-reading examples.
+
+## Training Data
+
+Each arm contains 5,801 training rows in a v0.21-equivalent source-screening
+mixture: 5,501 unchanged occurrences and 300 replacement occurrences. The
+replacement source for this model is **AIHub-71533, 기술과학 문서 기계독해 데이터**. The 300 examples
+were selected deterministically with seed 20260829; no quality, ranking,
+embedding, or model scoring was used for selection.
+
+Public evaluation benchmarks such as KMMLU-Pro, CLIcK, HLE, SNU Ko-MuSR,
+Com2-main, and Original MuSR were not used as SFT data. The applicable terms
+of the AI Hub source data remain in force.
+
+## Training Procedure
+
+- Objective: assistant-only causal-language-model cross entropy
+- Epochs: 1
+- Learning rate: 5e-5
+- Optimizer: adamw_torch_fused
+- Scheduler: linear, no warmup
+- Weight decay: 0.0
+- Maximum gradient norm: 1.0
+- LoRA: rank 16, alpha 32, dropout 0.05
+- LoRA target modules: q_proj, k_proj, v_proj, o_proj, gate_proj, up_proj, down_proj
+- Per-device batch size: 1
+- Gradient accumulation: 8 (effective batch size 8)
+- Maximum sequence length: 2048
+- Precision: BF16
+- Packing: disabled
+- Random seed: 42
+
+## Local Evaluation
+
+The full local canonical-suite evaluation used free and B1_constrained
+probes, 21,962 rows per model, and had zero generation errors. The following
+are the primary B1_constrained parsed-accuracy results; they are local
+evaluation results, not official K-AI leaderboard scores.
+
+KMMLU-Pro 39.40%, CLIcK 63.31%, HLE(Ko) 4.54%, SNU Ko-MuSR 56.80%, Com2-main(Ko) 51.60%; five-axis mean 43.13%.
+
+## Usage
+
+Load the repository with transformers AutoModelForCausalLM and
+AutoTokenizer, or directly with standard vLLM. The merged repository does
+not require a separate adapter or trust_remote_code.
+
+## Intended Use and Limitations
+
+This model is an experimental Korean SFT model for research and controlled
+evaluation. It can produce factual errors and should not be used as a
+substitute for professional legal, accounting, medical, or financial advice.
+
+## License
+
+The base model is distributed under the Apache License 2.0. The applicable
+terms of the AI Hub source data remain in force for use of the training data.
+See LICENSE for the base model license text.

chat_template.jinja

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+{%- if tools is iterable and tools | length > 0 %}
+                    {{- '<|im_start|><|system|>'}}
+                    {{- '당신은 도구 호출 기능을 갖춘 유용한 도우미입니다. 사용자의 요청을 처리하기 위해서 필요한 도구가 주어진 목록에 있는 경우 도구 호출로 응답하세요.
+필요한 도구가 목록에 없는 경우에는 도구 호출 없이 사용자가 요구한 정보를 제공하세요.
+필요한 도구가 목록에 있지만 해당 도구를 호출하는데 필요한 argument 정보가 부족한 경우 해당 정보를 사용자에게 요청하세요.
+사용자의 요청을 처리하기 위해 여러번 도구를 호출할 수 있어야 합니다.
+도구 호출 이후 도구 실행 결과를 입력으로 받으면 해당 결과를 활용하여 답변을 생성하세요.
+
+다음은 접근할 수 있는 도구들의 목록 입니다:
+<tools>
+'}}
+                    {%- for t in tools %}
+                        {{- t | tojson }}
+                        {{- '
+' }}
+                    {%- endfor %}
+                    {{- '</tools>' }}
+                    {{- '
+
+도구를 호출하려면 아래의 JSON으로 응답하세요.
+도구 호출 형식: <tool_call>{"name": 도구 이름, "arguments": dictionary 형태의 도구 인자값}</tool_call>' }}
+                    {{- '<|im_end|>' }}
+                {%- endif %}
+        
+                {%- for message in messages %}
+                    {%- if message.role == 'system' %}
+                        {{- '<|im_start|><|system|>' + message.content + '<|im_end|>'}}
+                    {%- elif message.role == 'user' %}
+                        {{- '<|im_start|><|user|>' + message.content + '<|im_end|>'}}
+                    {%- elif message.role == 'assistant' %}
+                        {{- '<|im_start|><|assistant|>'}}
+                        {%- set content = '' %}
+                        {%- if message.content is defined %}
+                            {%- set content = message.content %}
+                        {%- endif %}
+                        
+                {%- if add_generation_prompt and not (message.reasoning_content is defined and message.reasoning_content is not none) %}
+                    {%- if '</think>' in message.content %}
+                        {%- set content = message.content.split('</think>'.strip())[-1].lstrip('\n') %}
+                    {%- endif %}
+                {%- endif %}
+                
+                        {{- content}}
+                        {%- if message.tool_calls is defined %}
+                            {%- for tool_call in message.tool_calls %}
+                                {%- if tool_call.function is defined %}
+                                    {%- set tool_call = tool_call.function %}
+                                {%- endif %}
+                                {{- '<tool_call>' }}
+                                {{- '{' }}
+                                {{- '"name": "' }}
+                                {{- tool_call.name }}
+                                {{- '"' }}
+                                {%- if tool_call.arguments is defined %}
+                                    {{- ', ' }}
+                                    {{- '"arguments": ' }}
+                                    {{- tool_call.arguments|tojson }}
+                                {%- endif %}
+                                {{- '}' }}
+                                {{- '</tool_call>' }}
+                            {%- endfor %}
+                        {%- endif %}
+                        {{- '<|im_end|>'}}
+        
+                    {%- elif message.role == 'tool' %}
+                        {{- '<|im_start|><|extra_id_13|><tool_output>' + message.content + '</tool_output><|im_end|>'}}
+                    {%- endif %}
+                {%- endfor %}
+                
+                    {%- if add_generation_prompt %}
+                        {{- '<|im_start|><|assistant|>' }}
+                    {%- endif %}

config.json

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+{
+  "architectures": [
+    "LlamaForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.1,
+  "bos_token_id": 0,
+  "dtype": "bfloat16",
+  "eos_token_id": 0,
+  "head_dim": 128,
+  "hidden_act": "silu",
+  "hidden_size": 4096,
+  "initializer_range": 0.02,
+  "intermediate_size": 10880,
+  "max_position_embeddings": 32768,
+  "mlp_bias": false,
+  "model_type": "llama",
+  "num_attention_heads": 32,
+  "num_hidden_layers": 32,
+  "num_key_value_heads": 32,
+  "pad_token_id": null,
+  "pretraining_tp": 1,
+  "rms_norm_eps": 1e-05,
+  "rope_parameters": {
+    "rope_theta": 500000,
+    "rope_type": "default"
+  },
+  "tie_word_embeddings": false,
+  "transformers_version": "5.15.0",
+  "use_cache": false,
+  "vocab_size": 102400
+}

generation_config.json

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+{
+  "bos_token_id": 0,
+  "eos_token_id": 27,
+  "max_new_tokens": 32768,
+  "pad_token_id": 1,
+  "transformers_version": "5.15.0"
+}

kds_merge_info.json

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+{
+  "base_model": "AX-3.1-Light",
+  "base_model_path": "/home/youngseok3/.cache/huggingface/hub/models--skt--A.X-3.1-Light/snapshots/9b41bb2406472634d8812c0b8931fa40fa9a6c3a",
+  "adapter_path": "/home/youngseok3/KDS/experiments/source_screening_v021/outputs/source_screen_scitech_mrc_300"
+}

model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:26a8f1271d06f00275348ab16449349151bdcdd1eb4dd312c6ed3d3fdcc685e2
+size 14529635608

tokenizer_config.json

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+{
+  "add_prefix_space": false,
+  "backend": "tokenizers",
+  "bos_token": "<|endoftext|>",
+  "clean_up_tokenization_spaces": true,
+  "cls_token": "<|cls|>",
+  "eod_token": "<|endoftext|>",
+  "eos_token": "<|im_end|>",
+  "errors": "replace",
+  "is_local": true,
+  "local_files_only": true,
+  "mask_token": "<|mask|>",
+  "max_length": 7680,
+  "model_max_length": 32768,
+  "model_specific_special_tokens": {
+    "eod_token": "<|endoftext|>"
+  },
+  "pad_token": "<|pad|>",
+  "sep_token": "<|sep|>",
+  "tokenizer_class": "GPT2Tokenizer",
+  "unk_token": "<|unk|>",
+  "vocab_size": 102400
+}