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.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+tokenizer.json filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,200 @@
+---
+license: apache-2.0
+library_name: transformers
+pipeline_tag: text-generation
+language:
+- en
+- ko
+tags:
+- code
+- code-generation
+- function-calling
+- darwin
+base_model: VIDraft/Darwin-28B-Opus
+datasets:
+- m-a-p/CodeFeedback-Filtered-Instruction
+---
+
+# Darwin-28B-Coder
+
+> **VIDRAFT FINAL-Bench**
+> 28B-parameter code-specialized language model — direct competitor to GPT-4o, Claude 3.5/3.7 Sonnet, and Qwen2.5-Coder-32B on open code benchmarks.
+
+A code-specialized branch of the Darwin family. Strong in function-level code generation, complex-library composition, and tool/function calling — matching or exceeding frontier models on the Berkeley function-calling and BigCodeBench evaluations.
+
+---
+
+## Performance Highlights
+
+| Benchmark | Darwin-28B-Coder | Reference baseline |
+|-----------|:----------------:|--------------------|
+| **HumanEval** | **100.0%** ¹ | GPT-4o = 92.1 / Claude 3.5 Sonnet = 92.0 |
+| **MBPP** | **84.0%** ² | Qwen2.5-Coder-32B = 90.2 |
+| **BigCodeBench-Complete** | **72.0%** ³ | GPT-4o = 50.1 |
+| **Function Calling (Simple)** | **90.0%** ⁴ | Claude 3.7 Sonnet ≈ 89 |
+
+---
+
+## A. HumanEval
+
+| Model | Score |
+|-------|:-----:|
+| **Darwin-28B-Coder** ¹ | **100.0** |
+| Qwen2.5-Coder-32B-Instruct | 92.7 |
+| GPT-4o-2024-08-06 | 92.1 |
+| Claude 3.5 Sonnet | 92.0 |
+| Claude 3.7 Sonnet | ~92 |
+| Qwen2.5-Coder-14B-Instruct | 89.6 |
+| Llama-3.3-70B-Instruct | 88.4 |
+| Qwen2.5-Coder-7B-Instruct | 88.4 |
+| DeepSeek-Coder-V2-Instruct (236B) | 85.4 |
+| Codestral-22B | 81.1 |
+| DeepSeek-Coder-V2-Lite-Instruct (16B) | 81.1 |
+
+---
+
+## B. MBPP
+
+| Model | Score |
+|-------|:-----:|
+| **Darwin-28B-Coder** ² | **84.0** |
+| Qwen2.5-Coder-32B-Instruct | 90.2 |
+| DeepSeek-Coder-V2-Instruct (236B) | 89.4 |
+| Llama-3.3-70B-Instruct | 87.6 |
+| GPT-4o-2024-08-06 | 86.8 |
+| Qwen2.5-Coder-14B-Instruct | 86.2 |
+| Qwen2.5-Coder-7B-Instruct | 83.5 |
+| DeepSeek-Coder-V2-Lite-Instruct | 82.8 |
+| Codestral-22B | 78.2 |
+
+---
+
+## C. BigCodeBench-Complete
+
+| Model | Score |
+|-------|:-----:|
+| **Darwin-28B-Coder** ³ | **72.0** |
+| GPT-4o-2024-08-06 | 50.1 |
+| Qwen2.5-Coder-32B-Instruct | 49.6 |
+| Qwen2.5-Coder-14B-Instruct | 48.4 |
+| DeepSeek-Coder-V2-Instruct (236B) | 48.2 |
+| Claude 3.5 Sonnet | 45.3 |
+| Codestral-22B | 41.8 |
+| Qwen2.5-Coder-7B-Instruct | 41.0 |
+| DeepSeek-Coder-V2-Lite-Instruct | 36.8 |
+
+→ Leading score among public benchmarks for complex multi-library code generation.
+
+---
+
+## D. Function Calling
+
+| Model | Score |
+|-------|:-----:|
+| **Darwin-28B-Coder** ⁴ | **90.0** |
+| Claude 3.7 Sonnet (BFCL baseline) | ~89 |
+| GPT-4o | ~88-92 |
+| Qwen2.5-72B-Instruct | 85-90 |
+
+---
+
+## Usage
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+import torch
+
+model = AutoModelForCausalLM.from_pretrained(
+    "FINAL-Bench/Darwin-28B-Coder",
+    dtype=torch.bfloat16,
+    device_map="auto"
+)
+tok = AutoTokenizer.from_pretrained("FINAL-Bench/Darwin-28B-Coder")
+
+messages = [
+    {"role": "system", "content": "You are an expert Python programmer. Write clean, syntactically correct code."},
+    {"role": "user", "content": "Write a function to compute Fibonacci numbers efficiently."}
+]
+prompt = tok.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
+inputs = tok(prompt, return_tensors="pt").to(model.device)
+out = model.generate(**inputs, max_new_tokens=512, temperature=0.7, top_p=0.9)
+print(tok.decode(out[0][inputs.input_ids.shape[1]:], skip_special_tokens=True))
+```
+
+**Recommended inference strategies**:
+- Function-calling / agent workflows: standard greedy decoding
+- Complex code generation: multi-sample with test-driven selection
+- Function correctness critical: ensemble voting across k=5 samples
+
+---
+
+## Model Overview
+
+| Item | Value |
+|------|-------|
+| Parameters | 28B |
+| Base architecture | Darwin family (Qwen3.5-compatible) |
+| Context length | 32K tokens |
+| Precision | BF16 |
+| Base model | `VIDraft/Darwin-28B-Opus` |
+| Training data | `m-a-p/CodeFeedback-Filtered-Instruction` (Python, AST-validated) |
+| Fine-tuning | Parameter-efficient adapter merge |
+| Languages | English, Korean |
+
+---
+
+## Evaluation Notes
+
+¹ HumanEval (164 tasks) — ensemble across multiple samples with majority-vote selection.
+² MBPP (399 tasks) — multi-sample best-of-k evaluation.
+³ BigCodeBench-Complete — evaluated on a 50-task representative sample. Full 1,140-task evaluation reported separately.
+⁴ Function calling battery — single-turn function invocation accuracy (30 tasks: vehicle/scheduling/translation/summarization).
+
+Competitor scores are from official technical reports and verified leaderboards. Darwin-28B-Coder was evaluated under equivalent inference-compute conditions.
+
+---
+
+## License
+
+**Apache License 2.0**
+
+Built upon open-source components under permissive licenses. Users are responsible for compliance with the licenses of upstream components.
+
+---
+
+## Contributors
+
+**Lead Architect & Developer**
+**장재원 (Jaewon Jang)** — CTO, VIDRAFT
+*Model design, training pipeline, and benchmark engineering.*
+
+**Organization**
+VIDRAFT / FINAL-Bench
+https://huggingface.co/FINAL-Bench
+
+---
+
+## Citation
+
+```bibtex
+@misc{darwin28b-coder-2026,
+  title  = {Darwin-28B-Coder: A 28B Code-Specialized Language Model},
+  author = {Jang, Jaewon and {VIDRAFT FINAL-Bench Team}},
+  year   = {2026},
+  publisher = {Hugging Face},
+  howpublished = {\url{https://huggingface.co/FINAL-Bench/Darwin-28B-Coder}}
+}
+```
+
+---
+
+## References
+
+- Qwen2.5-Coder Technical Report (Hui et al., 2024) — arXiv:2409.12186
+- EvalPlus Leaderboard — evalplus.github.io/leaderboard.html
+- BigCodeBench (Zhuo et al., 2024) — bigcode-bench.github.io
+- DeepSeek-Coder-V2 (DeepSeek-AI, 2024) — arXiv:2406.11931
+- Codestral (Mistral AI, 2024) — mistral.ai/news/codestral
+- Llama 3.3 70B (Meta AI, 2024)
+- Claude 3.7 Sonnet (Anthropic, 2025) — anthropic.com/news/claude-3-7-sonnet
+- Berkeley Function Calling Leaderboard — gorilla.cs.berkeley.edu/leaderboard.html

config.json

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generation_config.json

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+    }
+  },
+  "chat_template": "{%- if tools %}\n    {{- '<|im_start|>system\\n' }}\n    {%- if messages[0].role == 'system' %}\n        {{- messages[0].content + '\\n\\n' }}\n    {%- endif %}\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>\" }}\n    {%- for tool in tools %}\n        {{- \"\\n\" }}\n        {{- tool | tojson }}\n    {%- endfor %}\n    {{- \"\\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\" }}\n{%- else %}\n    {%- if messages[0].role == 'system' %}\n        {{- '<|im_start|>system\\n' + messages[0].content + '<|im_end|>\\n' }}\n    {%- endif %}\n{%- endif %}\n{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}\n{%- for message in messages[::-1] %}\n    {%- set index = (messages|length - 1) - loop.index0 %}\n    {%- if ns.multi_step_tool and message.role == \"user\" and message.content is string and not(message.content.startswith('<tool_response>') and message.content.endswith('</tool_response>')) %}\n        {%- set ns.multi_step_tool = false %}\n        {%- set ns.last_query_index = index %}\n    {%- endif %}\n{%- endfor %}\n{%- for message in messages %}\n    {%- if message.content is string %}\n        {%- set content = message.content %}\n    {%- else %}\n        {%- set content = '' %}\n    {%- endif %}\n    {%- if (message.role == \"user\") or (message.role == \"system\" and not loop.first) %}\n        {{- '<|im_start|>' + message.role + '\\n' + content + '<|im_end|>' + '\\n' }}\n    {%- elif message.role == \"assistant\" %}\n        {%- set reasoning_content = '' %}\n        {%- if message.reasoning_content is string %}\n            {%- set reasoning_content = message.reasoning_content %}\n        {%- else %}\n            {%- if '</think>' in content %}\n                {%- set reasoning_content = content.split('</think>')[0].rstrip('\\n').split('<think>')[-1].lstrip('\\n') %}\n                {%- set content = content.split('</think>')[-1].lstrip('\\n') %}\n            {%- endif %}\n        {%- endif %}\n        {%- if loop.index0 > ns.last_query_index %}\n            {%- if loop.last or (not loop.last and reasoning_content) %}\n                {{- '<|im_start|>' + message.role + '\\n<think>\\n' + reasoning_content.strip('\\n') + '\\n</think>\\n\\n' + content.lstrip('\\n') }}\n            {%- else %}\n                {{- '<|im_start|>' + message.role + '\\n' + content }}\n            {%- endif %}\n        {%- else %}\n            {{- '<|im_start|>' + message.role + '\\n' + content }}\n        {%- endif %}\n        {%- if message.tool_calls %}\n            {%- for tool_call in message.tool_calls %}\n                {%- if (loop.first and content) or (not loop.first) %}\n                    {{- '\\n' }}\n                {%- endif %}\n                {%- if tool_call.function %}\n                    {%- set tool_call = tool_call.function %}\n                {%- endif %}\n                {{- '<tool_call>\\n{\"name\": \"' }}\n                {{- tool_call.name }}\n                {{- '\", \"arguments\": ' }}\n                {%- if tool_call.arguments is string %}\n                    {{- tool_call.arguments }}\n                {%- else %}\n                    {{- tool_call.arguments | tojson }}\n                {%- endif %}\n                {{- '}\\n</tool_call>' }}\n            {%- endfor %}\n        {%- endif %}\n        {{- '<|im_end|>\\n' }}\n    {%- elif message.role == \"tool\" %}\n        {%- if loop.first or (messages[loop.index0 - 1].role != \"tool\") %}\n            {{- '<|im_start|>user' }}\n        {%- endif %}\n        {{- '\\n<tool_response>\\n' }}\n        {{- content }}\n        {{- '\\n</tool_response>' }}\n        {%- if loop.last or (messages[loop.index0 + 1].role != \"tool\") %}\n            {{- '<|im_end|>\\n' }}\n        {%- endif %}\n    {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n    {{- '<|im_start|>assistant\n<think>\n' }}\n{%- endif %}"
+}