commit 6f16030901227f07d7bc374c02664aaed878ec40
Author: ModelHub XC <noreply@modelhub.org.cn>
Date:   Sat Jun 13 10:50:16 2026 +0800

    初始化项目，由ModelHub XC社区提供模型
    
    Model: rahimdzx/AraCode-7B-Full
    Source: Original Platform

diff --git a/.gitattributes b/.gitattributes
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diff --git a/README.md b/README.md
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+---
+language:
+- ar
+- en
+tags:
+- code
+- arabic
+- gguf
+- code-explanation
+- text-generation
+license: apache-2.0
+---
+
+# 🐪 AraCode-7B-GGUF
+
+**The first open-source Arabic-specialized code explanation and generation model.**
+
+AraCode-7B understands, explains, and generates code in Arabic — a capability no existing model provides with such precision. Whether you're a student learning to code, a developer working in Arabic, or a researcher exploring multilingual code AI, this model was built specifically for you.
+
+---
+
+## 🌟 What makes AraCode-7B different?
+
+Existing code models (CodeLlama, StarCoder, DeepSeek-Coder) generate excellent code but only communicate effectively in English. On the other hand, general Arabic LLMs (Jais, ALLaM, Falcon-Arabic) handle Arabic beautifully but were never natively optimized for strict coding tasks. 
+
+**AraCode-7B bridges this gap.** It combines robust Arabic linguistic capabilities with precise, executable code generation and strict instruction adherence.
+
+---
+
+## 📊 Comprehensive Benchmarks
+
+We evaluated **AraCode-7B** using both custom coding benchmarks and standardized frameworks (IFEval, AraGen) to compare its performance against the latest state-of-the-art Arabic and multilingual models.
+
+### 1. Code Generation & Understanding (Zero-Shot)
+Tested on a custom Arabic benchmark measuring raw coding capability, algorithmic logic, and debugging.
+
+| Model | Code Gen (%) | Explain (%) | Debug (%) | Translate NL->Code (%) | Total Score |
+|:---|:---:|:---:|:---:|:---:|:---:|
+| **AraCode-7B (Ours)** | **90.0%** | **92.5%** | **100.0%** | **94.0%** | **94.12%** |
+| ALLaM-7B-Instruct | 45.0% | 86.2% | 100.0% | 90.0% | 80.30% |
+
+> **Key Takeaway:** AraCode-7B achieves a massive **90% in executable Code Generation**. Unlike general conversational models that suffer from "excessive chatting" or infinite loops during generation, AraCode outputs clean, ready-to-run Python code efficiently.
+
+### 2. Instruction Following (IFEval - Arabic)
+Evaluated on strict instruction adherence (e.g., "output only code", "start with a specific word"). *Competitor scores are based on published strict 0-shot IFEval (ar) benchmarks.*
+
+| Model | IFEval (Arabic) (%) |
+|:---|:---:|
+| **AraCode-7B (Ours - Local Eval)** | **80.00%** |
+| Jais-2-8B | 37.92% |
+| Qwen2.5-7B-Instruct | 33.21% |
+| ALLaM-7B-Instruct-preview | 19.40% |
+| Llama-3.1-8B-Instruct | 10.87% |
+
+> **Key Takeaway:** AraCode-7B excels at instruction following. For developers, this means the model respects formatting constraints (like returning raw code without Markdown blocks) far better than general-purpose LLMs.
+
+### 3. Cultural Alignment & Safety (AraGen 3C3H Framework)
+Evaluated on Cultural awareness, Helpfulness, Harmlessness, Honesty, and Humility. *Competitor scores are based on published AraGen 12-24 benchmarks.*
+
+| Model | AraGen 3C3H Average (%) |
+|:---|:---:|
+| Jais-2-8B | 67.20% |
+| Qwen2.5-7B-Instruct | 53.20% |
+| **AraCode-7B (Ours - Local Eval)** | **50.00%** |
+| Llama-3.1-8B-Instruct | 40.65% |
+
+> **Key Takeaway:** AraCode-7B maintains a healthy balance (50%) in safety and cultural alignment. As a domain-specific model optimized for logic and programming, it successfully avoids the "alignment tax"—ensuring that strict conversational guardrails do not degrade its primary function as a coding assistant.
+
+---
+
+## 🚀 Quickstart
+
+You can easily run this model locally using popular GGUF tools.
+
+**Using llama.cpp:**
+```bash
+llama-cli -hf rahimdzx/AraCode-7B-GGUF --jinja
+```
+
+**Using Ollama:**
+```bash
+ollama run hf.co/rahimdzx/AraCode-7B-GGUF
+```
+
+**Using llama-cpp-python:**
+```python
+from llama_cpp import Llama
+
+llm = Llama.from_pretrained(
+    repo_id="rahimdzx/AraCode-7B-GGUF",
+    filename="aracode-7b.Q4_K_M.gguf",
+    n_gpu_layers=-1,
+    n_ctx=2048
+)
+
+response = llm.create_chat_completion(
+    messages=[
+        {"role": "user", "content": "اكتب دالة بايثون للبحث الثنائي (Binary Search)."}
+    ]
+)
+print(response["choices"][0]["message"]["content"])
+```
+
+---
+---
+
+## 💻 Example Usage
+
+**Input:**
+> اشرح الكود التالي بالعربية:
+> ```python
+> def binary_search(arr, target):
+>     lo, hi = 0, len(arr) - 1
+>     while lo <= hi:
+>         mid = (lo + hi) // 2
+>         if arr[mid] == target:
+>             return mid
+>         elif arr[mid] < target:
+>             lo = mid + 1
+>         else:
+>             hi = mid - 1
+>     return -1
+> ```
+
+**Output:**
+> ### شرح الكود باللغة العربية
+> 
+> #### 1. **تعريف الدالة**:
+> الدالة المعرفة في الكود تُدعى `binary_search`، والتي تستخدم للبحث عن عنصر معين في مصفوفة مرتبة.
+> 
+> #### 2. **المدخلات**:
+> - `arr`: هي المصفوفة المرتبة التي نبحث فيها عن العنصر.
+> - `target`: هو العنصر الذي نريد العثور عليه في المصفوفة.
+> 
+> #### 3. **المخرجات**:
+> الدالة تعيد الفهرس (index) للعنصر إذا تم العثور عليه، أو `-1` إذا لم يتم العثور عليه.
+> 
+> #### 4. **الخطوات**:
+> - **تثبيت الحدود**: نبدأ بتعريف متغيرين `lo` و `hi`، حيث `lo` يمثل بداية المصفوفة (0) و `hi` يمثل النهاية (طول المصفوفة - 1).
+> - **تكرار البحث**: نستخدم حلقة `while` للتحقق من أن `lo` أقل أو يساوي `hi`.
+> - **حساب النقطة الوسطى**: نحسب النقطة الوسطى `mid` باستخدام عملية القسمة الصحيحة `(lo + hi) // 2`.
+> - **مقارنة العنصر**: 
+>   - إذا كان `arr[mid] == target`، نعيد الفهرس `mid`.
+>   - إذا كان أقل، نبحث في النصف الأيمن (`lo = mid + 1`).
+>   - إذا كان أكبر، نبحث في النصف الأيسر (`hi = mid - 1`).
+> 
+> #### مثال عملي:
+> إذا كان لدينا المصفوفة `arr = [1, 2, 3, 4, 5, 6, 7, 8, 9]` والهدف `target = 5`، الدالة ستعيد الفهرس `4`.
+> 
+> #### ملخص:
+> تستخدم الدالة تقنية البحث الثنائي بكفاءة عالية وبتعقيد زمني O(log n)، مما يجعلها ممتازة للمصفوفات الكبيرة.
+Github :https://github.com/Rahimdzx/AraCode-7B
+## 📄 License
+This model is released under the **Apache 2.0** license.
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diff --git a/chat_template.jinja b/chat_template.jinja
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+{%- 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 %}
diff --git a/config.json b/config.json
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+++ b/config.json
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+{
+    "architectures": [
+        "Qwen2ForCausalLM"
+    ],
+    "attention_dropout": 0.0,
+    "bos_token_id": 151643,
+    "torch_dtype": "bfloat16",
+    "eos_token_id": 151645,
+    "hidden_act": "silu",
+    "hidden_size": 3584,
+    "initializer_range": 0.02,
+    "intermediate_size": 18944,
+    "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"
+    ],
+    "max_position_embeddings": 32768,
+    "max_window_layers": 28,
+    "model_type": "qwen2",
+    "num_attention_heads": 28,
+    "num_hidden_layers": 28,
+    "num_key_value_heads": 4,
+    "pad_token_id": 151665,
+    "rms_norm_eps": 1e-06,
+    "rope_parameters": {
+        "rope_theta": 1000000.0,
+        "rope_type": "default"
+    },
+    "sliding_window": null,
+    "tie_word_embeddings": false,
+    "unsloth_fixed": true,
+    "unsloth_version": "2026.4.2",
+    "use_cache": true,
+    "use_sliding_window": false,
+    "vocab_size": 152064
+}
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+}
diff --git a/tokenizer.json b/tokenizer.json
new file mode 100644
index 0000000..5340d81
--- /dev/null
+++ b/tokenizer.json
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:bd5948af71b4f56cf697f7580814c7ce8b80595ef985544efcacf716126a2e31
+size 11422356
diff --git a/tokenizer_config.json b/tokenizer_config.json
new file mode 100644
index 0000000..462a4ac
--- /dev/null
+++ b/tokenizer_config.json
@@ -0,0 +1,17 @@
+{
+  "add_prefix_space": false,
+  "backend": "tokenizers",
+  "bos_token": null,
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "<|im_end|>",
+  "errors": "replace",
+  "extra_special_tokens": [],
+  "is_local": false,
+  "model_max_length": 32768,
+  "pad_token": "<|PAD_TOKEN|>",
+  "padding_side": "right",
+  "split_special_tokens": false,
+  "tokenizer_class": "Qwen2Tokenizer",
+  "unk_token": null,
+  "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"
+}
\ No newline at end of file