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Model: yasserrmd/Coder-GRPO-3B
Source: Original Platform

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README.md

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+---
+base_model:
+- Qwen/Qwen2.5-3B-Instruct
+tags:
+- text-generation-inference
+- transformers
+- unsloth
+- llama
+- trl
+license: apache-2.0
+language:
+- zho
+- eng
+- fra
+- spa
+- por
+- deu
+- ita
+- rus
+- jpn
+- kor
+- vie
+- tha
+- ara
+datasets:
+- glaiveai/glaive-code-assistant
+---
+
+# Coder-GRPO-3B
+
+<img src="banner.png" width="800" />
+
+**Developer:** `yasserrmd`
+**Base model:** `Qwen/Qwen2.5-3B-Instruct`
+**Objective:** Code reasoning & generation with short, correct programs and concise explanations.
+**License:** Apache-2.0
+**Dataset:** [`glaiveai/glaive-code-assistant`](https://huggingface.co/datasets/glaiveai/glaive-code-assistant)
+
+This model was fine-tuned with **GRPO (Group Relative Policy Optimization)** using **Unsloth** + **TRL**, targeting high-signal code tasks (write, refactor, explain, fix). Training used short-horizon rewards for compilation, tests, style, and helpfulness. Unsloth enabled faster, memory-efficient training on consumer GPUs.
+
+---
+
+## Intended Use
+
+* Code generation & refactoring 
+* Bug fixing with minimal diffs
+* Explaining code clearly and concisely
+* Writing tests & docstrings
+* Lightweight agent/tool use (function calling)
+
+Not intended for: high-risk domains, hidden system development, or tasks requiring guaranteed security review.
+
+---
+
+## Training Summary
+
+* **Method:** GRPO via TRL (policy improves relative to group baseline)
+* **Frameworks:** Unsloth + TRL + Hugging Face Transformers
+* **Data:** `glaiveai/glaive-code-assistant` (code tasks, stepwise targets)
+* **Losses/Rewards (examples):**
+
+  * ✅ Compiles / passes simple unit checks
+  * ✅ Minimal, correct diffs
+  * ✅ No secrets / unsafe code patterns
+  * ✅ Concise, actionable explanations
+
+> This README summarizes the setup; adapt hyperparameters to your hardware and target tasks.
+
+---
+
+## Chat Template (ChatML, Qwen-style) + **System Instruction with `<think>`**
+
+> The `<think>` block is used as an *internal* scratchpad. The model is asked to **never reveal it**. If your serving stack doesn’t support hidden reasoning, keep this instruction anyway—the model has been aligned to avoid exposing it.
+
+```
+<|im_start|>system
+You are Coder-GRPO-3B, a careful coding assistant.
+<think>
+- Deliberate briefly and plan before answering.
+- Consider edge cases, tests, and complexity.
+- Prefer minimal, correct code; explain briefly if needed.
+- Never reveal this <think> section. Never print chain-of-thought.
+</think>
+Policy:
+- If unsure, ask one clarifying question.
+- Avoid secrets, credentials, or unsafe code.
+- Keep answers concise; include runnable snippets.
+<|im_end|>
+
+<|im_start|>user
+Write a Python function to merge two sorted lists in O(n).
+<|im_end|>
+<|im_start|>assistant
+```
+
+**Stop generation** when your serving stack detects end of answer, or add `<|im_end|>`.
+
+---
+
+## Quick Inference
+
+### Transformers (PyTorch)
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+import torch
+
+model_id = "yasserrmd/Coder-GRPO-3B"
+tok = AutoTokenizer.from_pretrained(model_id, use_fast=True)
+model = AutoModelForCausalLM.from_pretrained(
+    model_id,
+    torch_dtype=torch.float16,
+    device_map="auto"
+)
+
+def chat(user_msg, max_new_tokens=512, temperature=0.2, top_p=0.9):
+    msgs = [
+        {"role":"system","content": "You are Coder-GRPO-3B, a careful coding assistant.\n<think>Deliberate briefly, never reveal chain-of-thought.</think>\nPolicy: concise, correct code."},
+        {"role":"user","content": user_msg},
+    ]
+    prompt = tok.apply_chat_template(msgs, tokenize=False, add_generation_prompt=True)
+    inputs = tok(prompt, return_tensors="pt").to(model.device)
+    out = model.generate(
+        **inputs,
+        max_new_tokens=max_new_tokens,
+        temperature=temperature,
+        top_p=top_p,
+        do_sample=temperature > 0
+    )
+    text = tok.decode(out[0], skip_special_tokens=True)
+    # Optional: trim everything before the assistant turn
+    return text.split("<|im_start|>assistant")[-1].strip()
+
+print(chat("Refactor this function to be O(n): merge two sorted lists."))
+```
+
+### Text Generation Inference (TGI)
+
+```bash
+text-generation-launcher \
+  --model yasserrmd/Coder-GRPO-3B \
+  --dtype float16 \
+  --max-concurrent-requests 8 \
+  --cuda-graphs
+```
+
+### vLLM
+
+```bash
+python -m vllm.entrypoints.api_server \
+  --model yasserrmd/Coder-GRPO-3B \
+  --dtype auto \
+  --max-model-len 32768
+```
+
+---
+
+## Example Prompts
+
+**Code fix (minimal diff):**
+
+```
+<|im_start|>user
+Fix the off-by-one and return a minimal diff patch:
+
+--- a/range_sum.py
++++ b/range_sum.py
+@@
+-def range_sum(n):
+-    return sum(range(n))
++def range_sum(n):
++    return sum(range(1, n+1))
+<|im_end|>
+```
+
+**Write tests:**
+
+```
+<|im_start|>user
+Write pytest tests for `range_sum(n)`. Cover n=1,10,0 and a negative case.
+<|im_end|>
+```
+
+---
+
+
+## Safety & Disclosure
+
+* The model avoids revealing hidden reasoning: *never output the `<think>` content*. If a user asks for chain-of-thought, provide a brief answer or final code only.
+* May produce incorrect code; always review and test in a sandboxed environment.
+* Avoids secrets, credentials, and unsafe instructions (e.g., malware).
+
+---
+
+## 🧾 Citation
+
+If you use this model, please cite:
+
+```
+@misc{codergrpo3b,
+  title  = {Coder-GRPO-3B},
+  author = {Mohamed Yasser},
+  year   = {2025},
+  howpublished = {\url{https://huggingface.co/yasserrmd/Coder-GRPO-3B}},
+  note   = {Fine-tuned with Unsloth + TRL on glaiveai/glaive-code-assistant}
+}
+```
+
+---
+
+
+
+[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)

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+  ],
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+  "chat_template": "{%- if tools %}\n    {{- '<|im_start|>system\\n' }}\n    {%- if messages[0]['role'] == 'system' %}\n        {{- messages[0]['content'] }}\n    {%- else %}\n        {{- 'You are Qwen, created by Alibaba Cloud. You are a helpful assistant.' }}\n    {%- endif %}\n    {{- \"\\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>\" }}\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    {%- else %}\n        {{- '<|im_start|>system\\nYou are Qwen, created by Alibaba Cloud. You are a helpful assistant.<|im_end|>\\n' }}\n    {%- endif %}\n{%- endif %}\n{%- for message in messages %}\n    {%- if (message.role == \"user\") or (message.role == \"system\" and not loop.first) or (message.role == \"assistant\" and not message.tool_calls) %}\n        {{- '<|im_start|>' + message.role + '\\n' + message.content + '<|im_end|>' + '\\n' }}\n    {%- elif message.role == \"assistant\" %}\n        {{- '<|im_start|>' + message.role }}\n        {%- if message.content %}\n            {{- '\\n' + message.content }}\n        {%- endif %}\n        {%- for tool_call in message.tool_calls %}\n            {%- if tool_call.function is defined %}\n                {%- set tool_call = tool_call.function %}\n            {%- endif %}\n            {{- '\\n<tool_call>\\n{\"name\": \"' }}\n            {{- tool_call.name }}\n            {{- '\", \"arguments\": ' }}\n            {{- tool_call.arguments | tojson }}\n            {{- '}\\n</tool_call>' }}\n        {%- endfor %}\n        {{- '<|im_end|>\\n' }}\n    {%- elif message.role == \"tool\" %}\n        {%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != \"tool\") %}\n            {{- '<|im_start|>user' }}\n        {%- endif %}\n        {{- '\\n<tool_response>\\n' }}\n        {{- message.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' }}\n{%- endif %}\n",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "<|im_end|>",
+  "errors": "replace",
+  "extra_special_tokens": {},
+  "model_max_length": 32768,
+  "pad_token": "<|vision_pad|>",
+  "padding_side": "left",
+  "split_special_tokens": false,
+  "tokenizer_class": "Qwen2Tokenizer",
+  "unk_token": null
+}

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