初始化项目，由ModelHub XC社区提供模型

Model: Khurram123/Shaheen-3B-Kulliyat-e-Iqbal
Source: Original Platform

.gitattributes

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README.md

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+---
+license: apache-2.0
+base_model: Qwen/Qwen2.5-3B-Instruct
+datasets:
+- Khurram123/kulliyat-e-iqbal-shaheen
+tags:
+- iqbaliat
+- urdu-poetry
+- persian-poetry
+- philosophy
+- sufism
+- unsloth
+- qwen
+- shaheen
+- conversational
+language:
+- ur
+- fa
+metrics:
+- loss
+library_name: transformers
+pipeline_tag: text-generation
+model_name: Shaheen-Qwen2.5-3B-Kulliyat-e-Iqbal
+---
+
+<p align="center">
+  <br>
+  <b style="font-size: 26px;">"تو شاہیں ہے، پرواز ہے کام تیرا"</b> <br>
+  <b style="font-size: 18px;">— علامہ اقبال کے کلام اور فلسفے پر مبنی پہلا سپیشلائزڈ لسانی ماڈل</b>
+</p>
+
+<p align="center">
+  <img src="https://huggingface.co/Khurram123/Shaheen-3B-Kulliyat-e-Iqbal/resolve/main/image1.png" width="450" alt="Shaheen Iqbal Model Logo">
+</p>
+
+<h1 align="center">🦅 Shaheen-Qwen2.5-3B-Kulliyat-e-Iqbal (v1.0) 🇵🇰</h1>
+
+**Shaheen-Qwen2.5-3B** is a specialized Large Language Model fine-tuned on the complete poetic works of **Allama Muhammad Iqbal**. Built on the **Qwen 2.5 3B Instruct** architecture, this model is designed to interpret, explain, and contextualize the philosophical depth of **Iqbaliyat** in both Urdu and Persian.
+
+Using the **Kulliyat-e-Iqbal Shaheen Dataset** (11,659 records), this model bridges the gap between classical wisdom and modern conversational AI.
+
+---
+
+## 🌟 Model Highlights
+- **Specialized Knowledge:** Deeply trained on 11 major Urdu and Persian books of Allama Iqbal.
+- **Bilingual Proficiency:** Capable of understanding and explaining Persian (Farsi) couplets in simple Urdu.
+- **Philosophical Insight:** Optimized to discuss core concepts like **Khudi (Selfhood)**, **Ishq (Divine Love)**, and **Shaheen (The Eagle)**.
+- **Lightweight & Efficient:** 3 Billion parameters ensure lightning-fast inference on consumer-grade hardware (like RTX 4060 Ti).
+- **Optimization:** Fine-tuned using **Unsloth** with 4-bit LoRA for maximum performance with minimum VRAM footprint.
+
+---
+
+## 📊 Training Details
+- **Base Model:** `unsloth/qwen2.5-3b-instruct-bnb-4bit`
+- **Dataset Size:** 11,659 Rows (Instruction-Response Pairs)
+- **Epochs:** 1.37
+- **Final Train Loss:** 1.39
+- **Hardware:** NVIDIA GeForce RTX 4060 Ti (16GB)
+- **Software:** Ubuntu Linux + Unsloth AI
+
+---
+
+## 📚 Dataset Composition
+The model has "read" and analyzed the entire poetic corpus:
+| Language | Primary Books Included |
+| :--- | :--- |
+| **Urdu** | Bang-e-Dara, Bal-e-Jibreel, Zarb-e-Kaleem, Armaghan-e-Hijaz (Urdu) |
+| **Persian** | Asrar-e-Khudi, Rumuz-e-Bekhudi, Payam-e-Mashriq, Zabur-e-Ajam, Javid Nama, Pas Cha Bayad Kard |
+
+---
+
+## 🚀 How to Use (Inference)
+
+### Via Transformers & Unsloth
+```python
+from unsloth import FastLanguageModel
+import torch
+
+model, tokenizer = FastLanguageModel.from_pretrained(
+    model_name = "Khurram123/Shaheen-3B-Kulliyat-e-Iqbal",
+    max_seq_length = 2048,
+    load_in_4bit = True,
+)
+FastLanguageModel.for_inference(model)
+
+prompt = "علامہ اقبال کے تصورِ خودی کا پیغام کیا ہے؟"
+inputs = tokenizer([f"<|im_start|>user\n{prompt}<|im_end|>\n<|im_start|>assistant\n"], return_tensors="pt").to("cuda")
+
+outputs = model.generate(**inputs, max_new_tokens=250, temperature=0.5)
+print(tokenizer.batch_decode(outputs)[0])

adapter_config.json

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+{
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+  "alpha_pattern": {},
+  "arrow_config": null,
+  "auto_mapping": {
+    "base_model_class": "Qwen2ForCausalLM",
+    "parent_library": "transformers.models.qwen2.modeling_qwen2",
+    "unsloth_fixed": true
+  },
+  "base_model_name_or_path": "unsloth/qwen2.5-3b-instruct-bnb-4bit",
+  "bias": "none",
+  "corda_config": null,
+  "ensure_weight_tying": false,
+  "eva_config": null,
+  "exclude_modules": null,
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 32,
+  "lora_bias": false,
+  "lora_dropout": 0,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "peft_version": "0.18.1",
+  "qalora_group_size": 16,
+  "r": 32,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "k_proj",
+    "q_proj",
+    "o_proj",
+    "v_proj",
+    "up_proj",
+    "down_proj",
+    "gate_proj"
+  ],
+  "target_parameters": null,
+  "task_type": "CAUSAL_LM",
+  "trainable_token_indices": null,
+  "use_dora": false,
+  "use_qalora": false,
+  "use_rslora": false
+}

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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 %}

config.json

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+    "architectures": [
+        "Qwen2ForCausalLM"
+    ],
+    "attention_dropout": 0.0,
+    "torch_dtype": "bfloat16",
+    "eos_token_id": 151645,
+    "hidden_act": "silu",
+    "hidden_size": 2048,
+    "initializer_range": 0.02,
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+        "full_attention",
+        "full_attention",
+        "full_attention",
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+        "full_attention",
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+        "full_attention",
+        "full_attention",
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+        "full_attention",
+        "full_attention",
+        "full_attention",
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+    "model_type": "qwen2",
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+    "tie_word_embeddings": true,
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+}

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+  "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"
+}