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

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])