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Model: SeaFill2025/Qwen3-4B-SFT
Source: Original Platform

.gitattributes

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README.md

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+---
+language:
+  - en
+  - zh
+license: apache-2.0
+library_name: transformers
+pipeline_tag: text-generation
+tags:
+  - qwen3
+  - causal-lm
+  - supervised-fine-tuning
+  - math
+  - reasoning
+  - code
+  - science
+base_model: Qwen/Qwen3-4B-Base
+model-index:
+  - name: Qwen3-4B-SFT
+    results:
+      - task:
+          type: text-generation
+        dataset:
+          name: AIME 2024
+          type: aime2024
+        metrics:
+          - name: accuracy
+            type: accuracy
+            value: 20.8
+      - task:
+          type: text-generation
+        dataset:
+          name: AIME 2025
+          type: aime2025
+        metrics:
+          - name: accuracy
+            type: accuracy
+            value: 19.4
+      - task:
+          type: text-generation
+        dataset:
+          name: AMC 2023
+          type: amc2023
+        metrics:
+          - name: accuracy
+            type: accuracy
+            value: 58.0
+      - task:
+          type: text-generation
+        dataset:
+          name: GPQA-Diamond
+          type: gpqa_diamond
+        metrics:
+          - name: accuracy
+            type: accuracy
+            value: 29.1
+---
+
+## Qwen3-4B-SFT:
+
+Qwen3-4B-SFT is a reasoning-focused model derived from Qwen3-4B-Base via full-parameter fine-tuning on the verl framework. 
+
+There is a notable shortage of reproducible 'warm-start' SFT bases in open-source practice, this model bridges the gap between base models and reinforcement learning models. Optimally aligned for Chain-of-Thought (CoT) and instruction following, it serves as a robust warm-start for Reinforcement Learning.
+
+| Dataset | Base (4B)† | Qwen3-4B-SFT (this model) | Improvement |
+| :--- | :---: | :---: | :---: |
+| **AIME 2024** | 11.25% | **20.8%** | +9.55% |
+| **AIME 2025** | 6.46% | **19.4%** | +12.94% |
+| **AMC 2023** | 31.09% | **58.0%** | +26.91% |
+| **GPQA-Diamond** | 7.77% | **29.1%** | +21.33% |
+
+† Base (4B) figures are taken from [ (arXiv:2602.10885)](https://arxiv.org/pdf/2602.10885).
+
+- Dataset card used for SFT: https://huggingface.co/datasets/96kevinli29/SFT-Dataset
+
+## Qwen3-style reasoning and instruction following
+
+Minimal pattern (illustrative):
+
+```text
+<|im_start|>user
+… Among options A–D, which is correct? Reason step by step and put the final letter in \boxed{}.
+<|im_end|>
+
+<|im_start|>assistant
+<think>
+Compare A vs B vs C vs D against the stem; eliminate …; D remains consistent with …
+</think>
+Step-by-step: … (short derivation in the visible channel)
+Final answer: \boxed{D}
+<|im_end|>
+```
+Use a large enough **`max_new_tokens`** on hard math so both the **reasoning block** and the **visible** `\boxed{…}` line fit before generation stops.
+
+## Configuration Notes
+
+- Template: Trained with the **Qwen chat template**; learns to end responses with `<|im_end|>` (151645).
+- Suggested Configuration:
+  ```json
+  {
+    "eos_token_id": 151645
+  }
+  ```
+You may adjust settings according to your training or deployment needs.
+
+## Training Infrastructure
+
+- Cluster: MeluXina Supercomputer (LuxProvide)
+- Node Config: 4 NVIDIA-A100 GPUs per node.
+- Final SFT Run: 12 Node-hours (16× A100 for 3 hours)
+- Total R&D Investment: ~700 Node-hours (Includes data ablation, hyperparameter sweeps, and extensive benchmark evaluation.)
+
+## Project Links
+
+- Training code repository: https://github.com/96kevinli29/base-model-sft-verl
+
+## Limitations
+
+- Not optimized for factual correctness in all domains
+- May still produce hallucinations or unsafe outputs
+- Performance is sensitive to prompt style and decoding settings
+
+## Citation
+
+If you use this model, please cite **this checkpoint**, bibTeX for this release :
+
+```bibtex
+@misc{qwen3-4b-sft-2026,
+  title        = {{Qwen3-4B-SFT}: Supervised Fine-Tuned {Qwen3}-4B for Reasoning},
+  author       = {Hongyang Li, Xiao Li and {Sea-Fill Community}},
+  year         = {2026},
+  publisher    = {Hugging Face},
+  howpublished = {\url{https://huggingface.co/SeaFill2025/Qwen3-4B-SFT}},
+  note         = {Checkpoint trained with verl; warm-start for pre-RL alignment research. Maintained by Sea-Fill Community.}
+}
+```

chat_template.jinja

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+{%- if tools %}
+    {{- '<|im_start|>system\n' }}
+    {%- if messages[0].role == 'system' %}
+        {{- messages[0].content + '\n\n' }}
+    {%- endif %}
+    {{- "# 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' }}
+    {%- endif %}
+{%- endif %}
+{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}
+{%- for message in messages[::-1] %}
+    {%- set index = (messages|length - 1) - loop.index0 %}
+    {%- if ns.multi_step_tool and message.role == "user" and not(message.content.startswith('<tool_response>') and message.content.endswith('</tool_response>')) %}
+        {%- set ns.multi_step_tool = false %}
+        {%- set ns.last_query_index = index %}
+    {%- endif %}
+{%- endfor %}
+{%- for message in messages %}
+    {%- if (message.role == "user") or (message.role == "system" and not loop.first) %}
+        {{- '<|im_start|>' + message.role + '\n' + message.content + '<|im_end|>' + '\n' }}
+    {%- elif message.role == "assistant" %}
+        {%- set content = message.content %}
+        {%- set reasoning_content = '' %}
+        {%- if message.reasoning_content is defined and message.reasoning_content is not none %}
+            {%- set reasoning_content = message.reasoning_content %}
+        {%- else %}
+            {%- if '</think>' in message.content %}
+                {%- set content = message.content.split('</think>')[-1].lstrip('\n') %}
+                {%- set reasoning_content = message.content.split('</think>')[0].rstrip('\n').split('<think>')[-1].lstrip('\n') %}
+            {%- endif %}
+        {%- endif %}
+        {%- if loop.index0 > ns.last_query_index %}
+            {%- if loop.last or (not loop.last and reasoning_content) %}
+                {{- '<|im_start|>' + message.role + '\n<think>\n' + reasoning_content.strip('\n') + '\n</think>\n\n' + content.lstrip('\n') }}
+            {%- else %}
+                {{- '<|im_start|>' + message.role + '\n' + content }}
+            {%- endif %}
+        {%- else %}
+            {{- '<|im_start|>' + message.role + '\n' + content }}
+        {%- endif %}
+        {%- if message.tool_calls %}
+            {%- for tool_call in message.tool_calls %}
+                {%- if (loop.first and content) or (not loop.first) %}
+                    {{- '\n' }}
+                {%- endif %}
+                {%- if tool_call.function %}
+                    {%- set tool_call = tool_call.function %}
+                {%- endif %}
+                {{- '<tool_call>\n{"name": "' }}
+                {{- tool_call.name }}
+                {{- '", "arguments": ' }}
+                {%- if tool_call.arguments is string %}
+                    {{- tool_call.arguments }}
+                {%- else %}
+                    {{- tool_call.arguments | tojson }}
+                {%- endif %}
+                {{- '}\n</tool_call>' }}
+            {%- endfor %}
+        {%- endif %}
+        {{- '<|im_end|>\n' }}
+    {%- elif message.role == "tool" %}
+        {%- if loop.first 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' }}
+    {%- if enable_thinking is defined and enable_thinking is false %}
+        {{- '<think>\n\n</think>\n\n' }}
+    {%- endif %}
+{%- endif %}

config.json

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+{
+  "architectures": [
+    "Qwen3ForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "bos_token_id": null,
+  "dtype": "bfloat16",
+  "eos_token_id": 151645,
+  "head_dim": 128,
+  "hidden_act": "silu",
+  "hidden_size": 2560,
+  "initializer_range": 0.02,
+  "intermediate_size": 9728,
+  "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": 36,
+  "model_type": "qwen3",
+  "num_attention_heads": 32,
+  "num_hidden_layers": 36,
+  "num_key_value_heads": 8,
+  "pad_token_id": 151643,
+  "rms_norm_eps": 1e-06,
+  "rope_parameters": {
+    "rope_theta": 1000000,
+    "rope_type": "default"
+  },
+  "sliding_window": null,
+  "tie_word_embeddings": true,
+  "transformers_version": "5.3.0",
+  "use_cache": true,
+  "use_sliding_window": false,
+  "vocab_size": 151936
+}

generation_config.json

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+{
+  "bos_token_id": 151643,
+  "do_sample": false,
+  "eos_token_id": 151645,
+  "max_new_tokens": 2048,
+  "transformers_version": "5.3.0"
+}

model.safetensors

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tokenizer.json

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tokenizer_config.json

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+{
+  "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,
+  "pad_token": "<|endoftext|>",
+  "split_special_tokens": false,
+  "tokenizer_class": "Qwen2Tokenizer",
+  "unk_token": null
+}