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Model: ilkayO/Karga-2B-Thinking
Source: Original Platform

.gitattributes

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README.md

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+---
+language:
+- tr
+pipeline_tag: text-generation
+tags:
+- thinking
+- chain-of-thought
+- slm
+- turkish
+- edge-ai
+license: apache-2.0
+widget:
+- text: "Bir tarlada 5 koyun ve 3 tavuk vardır. Toplam kaç ayak vardır? Adım adım hesapla."
+  example_title: Matematik (Math)
+- text: "İki sayıyı toplayan 'sum_two' adında bir Python fonksiyonu yazın."
+  example_title: Kodlama (Python)
+- text: "Eğer bugün salı ise, 15 gün sonra hangi gün olur? Lütfen mantığını açıkla."
+  example_title: Mantık (Logic)
+base_model:
+- vngrs-ai/Kumru-2B
+---
+
+<div align="center">
+  <img src="https://huggingface.co/ilkayO/Karga-2B-Thinking/resolve/main/karga.png" width="180"/>
+  <h1>Karga-2B-Thinking 🐦‍⬛</h1>
+  <p><b>Turkish SLM with Chain-of-Thought reasoning · 2 billion parameters · Edge-friendly</b></p>
+  <p><i>A fine-tune of <a href="https://huggingface.co/vngrs-ai/Kumru-2B">Kumru-2B</a> that thinks out loud before answering.</i></p>
+
+[![Hugging Face Spaces](https://img.shields.io/badge/🤗%20Hugging%20Face-Live%20Demo-blue)](https://huggingface.co/spaces/ilkayO/Karga-Thinking-Demo)
+[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/ilkay-onay/karga-reasoning/blob/main/notebooks/Karga_Quickstart.ipynb)
+[![GitHub](https://img.shields.io/badge/GitHub-Source%20Code-black?logo=github)](https://github.com/ilkay-onay/karga-reasoning)
+[![Apache 2.0](https://img.shields.io/badge/License-Apache%202.0-green)](https://opensource.org/licenses/Apache-2.0)
+</div>
+
+**Karga-2B-Thinking** is an advanced fine-tune of the `vngrs-ai/Kumru-2B` base model. Just as crows (Karga) are known for their exceptional problem-solving skills and tool use, this model has been explicitly engineered to bring **Chain-of-Thought (CoT)** reasoning capabilities to a 2-Billion parameter Small Language Model (SLM) for the Turkish language. 
+
+By generating `<think> ... </think>` block before answering, the model significantly reduces hallucinations and logically plans its outputs, making it highly effective for mathematics, logic puzzles, and code generation on Edge devices.
+
+> ⚠️ **Academic Pre-Publication Notice** 
+> *This model serves as the official checkpoint for an ongoing academic research project. While the model weights are fully open-source (Apache 2.0), the proprietary synthetic dataset and the novel **"Deterministic Tensor Injection Agent"** training/inference architecture are temporarily withheld pending double-blind peer review. Full resources will be released upon publication.*
+
+## 🚀 Model Details
+- **Architecture:** MistralForCausalLM (Kumru-2B)
+- **Task:** Causal Language Modeling with CoT
+- **Parameters:** 2 Billion (Optimized for Edge AI)
+- **Language:** Turkish
+- **License:** Apache 2.0 (Commercially friendly)
+
+## 📊 Performance & Training
+Large Language Models often struggle with complex logic in low-resource languages. To overcome this, the model was trained using **QLoRA/Unsloth** on a highly robust, custom-translated synthetic dataset generated via vLLM pipelines. 
+
+On a strictly unseen benchmark of 654 complex questions, the fine-tuning process yielded massive improvements:
+- **Mathematics:** 10x Performance Increase (0.49% ➔ 4.93%)
+- **Python Coding:** +11.47% Boost (86.89% ➔ 98.36%)
+- **Overall Average:** Increased from 21.71% to 24.31%
+
+## 💻 Quick Usage
+You can easily integrate this model into your Python projects. The model uses a specific chat template and outputs its reasoning inside `<think>` tags.
+
+```python
+import torch
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model_id = "ilkayO/Karga-2B-Thinking"
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+model = AutoModelForCausalLM.from_pretrained(
+    model_id, 
+    device_map="auto", 
+    torch_dtype=torch.bfloat16
+)
+
+prompt = "Aylin'in yaşı, Burak'ın yaşının iki katıdır. Burak 12 yaşında ise, ikisinin yaşları toplamı kaçtır?"
+messages = [
+    {"role": "system", "content": "Adın Karga. Soruları mantıklı ve adım adım düşünerek yanıtla."},
+    {"role": "user", "content": prompt}
+]
+
+inputs = tokenizer.apply_chat_template(messages, return_tensors="pt", add_generation_prompt=True).to(model.device)
+
+with torch.no_grad():
+    outputs = model.generate(
+        inputs, 
+        max_new_tokens=1024, 
+        temperature=0.6, 
+        top_p=0.9, 
+        repetition_penalty=1.1
+    )
+
+response = tokenizer.decode(outputs[0][inputs.shape[-1]:], skip_special_tokens=True)
+print(response)
+```
+
+## 🤝 Commercial Integration & Consulting
+This model is open-sourced under the **Apache 2.0** license, meaning you are free to use, modify, and integrate it into your commercial products. 
+
+If your company is looking to integrate advanced NLP systems, build Agentic AI workflows, deploy Edge AI models, or if you are interested in having me join your AI team, feel free to reach out!
+
+📧 **Contact:** ilkayonay2001@gmail.com | [LinkedIn](https://linkedin.com/in/ilkay-onay-391905254)

chat_template.jinja

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+{{ bos_token }}
+{% set default_system = "Adın Karga. Soruları mantıklı ve adım adım düşünerek yanıtla." %}
+{% if messages[0]['role'] != 'system' %}
+    {{ '<|start_header_id|>system<|end_header_id|>\n\n' + default_system + '<|eot_id|>' }}
+{% endif %}
+{% for message in messages %}
+    {{ '<|start_header_id|>' + message['role'] + '<|end_header_id|>\n\n' + message['content'] | trim + '<|eot_id|>' }}
+{% endfor %}
+{% if add_generation_prompt %}
+    {{ '<|start_header_id|>assistant<|end_header_id|>\n\n<think>\n' }}
+{% endif %}

config.json

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+{
+    "architectures": [
+        "MistralForCausalLM"
+    ],
+    "attention_dropout": 0.0,
+    "bos_token_id": 2,
+    "torch_dtype": "bfloat16",
+    "eos_token_id": 3,
+    "head_dim": 128,
+    "hidden_act": "silu",
+    "hidden_size": 3072,
+    "initializer_range": 0.02,
+    "intermediate_size": 10752,
+    "max_position_embeddings": 8192,
+    "model_type": "mistral",
+    "num_attention_heads": 16,
+    "num_hidden_layers": 18,
+    "num_key_value_heads": 4,
+    "pad_token_id": 0,
+    "rms_norm_eps": 1e-05,
+    "rope_scaling": null,
+    "rope_theta": 500000,
+    "sliding_window": null,
+    "tie_word_embeddings": false,
+    "unsloth_version": "2026.4.4",
+    "use_cache": true,
+    "vocab_size": 50176
+}

model.safetensors

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+version https://git-lfs.github.com/spec/v1
+oid sha256:5083fd82219ed3ee89dd70a2d5215bb3aed74c50e911c11996710bbd37d7bb98
+size 4750295696

special_tokens_map.json

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+{
+  "bos_token": {
+    "content": "<BOS>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "eos_token": {
+    "content": "<EOS>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": {
+    "content": "<PAD>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "unk_token": {
+    "content": "<UNK>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}