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README.md

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 ---
 license: apache-2.0
+license_link: https://www.apache.org/licenses/LICENSE-2.0
+
+language:
+- en
+
+base_model:
+- Qwen/Qwen3-4B
+
+datasets:
+- HuggingFaceTB/smoltalk
+- agentica-org/DeepCoder-Preview-Dataset
+
+pipeline_tag: text-generation
+library_name: transformers
+
+tags:
+- qwen3
+- computer-science
+- software-engineering
+- programming
+- python
+- code-generation
+- debugging
+- transformers
+- pytorch
 ---
+
+# Qwen3-4B-Computer-Science
+
+Qwen3-4B-Computer-Science is a supervised fine-tuned language model based on **Qwen/Qwen3-4B**, designed for computer science and software engineering tasks.
+
+This repository contains the merged BF16 checkpoint compatible with the Hugging Face Transformers ecosystem.
+
+---
+
+# Model Summary
+
+The model specializes in programming-oriented instruction following across multiple computer science domains, including software engineering, debugging, algorithms, testing, and technical reasoning.
+
+Training was performed using parameter-efficient supervised fine-tuning (LoRA). The released checkpoint contains merged BF16 weights and can be used directly without PEFT adapters.
+
+---
+
+# Motivation
+
+General-purpose language models provide strong performance across many domains but are not specifically optimized for computer science workflows.
+
+Qwen3-4B-Computer-Science aims to improve programming-oriented instruction following while preserving the capabilities of the original Qwen3-4B base model.
+
+---
+
+# Model Details
+
+| Field | Value |
+|------|------|
+| Model Name | Qwen3-4B-Computer-Science |
+| Base Model | [Qwen/Qwen3-4B](https://huggingface.co/Qwen/Qwen3-4B) |
+| Model Type | Causal Language Model |
+| Architecture | Decoder-only Transformer |
+| Parameters | 4 Billion |
+| Fine-Tuning | Supervised Fine-Tuning (SFT) |
+| Fine-Tuning Method | LoRA |
+| Training Strategy | Distributed Data Parallel (DDP) |
+| Released Weights | Merged BF16 |
+| Framework | Hugging Face Transformers |
+| Primary Language | English |
+
+---
+
+# Training
+
+Training was performed using supervised fine-tuning (SFT) with parameter-efficient fine-tuning (LoRA).
+
+Optimization utilized Distributed Data Parallel (DDP). After training, the LoRA adapters were merged into the base model to produce the released BF16 checkpoint.
+
+The published model does not require PEFT adapters during inference.
+
+---
+
+# Training Data
+
+The final training corpus contains **60,989** training examples and **512** evaluation examples.
+
+| Dataset | Configuration | License | Train | Eval |
+|---------|--------------|---------|------:|-----:|
+| HuggingFaceTB/smoltalk | smol-magpie-ultra | Apache-2.0 | 49,584 | 416 |
+| agentica-org/DeepCoder-Preview-Dataset | primeintellect | MIT | 11,405 | 96 |
+
+---
+
+# Dataset Attribution
+
+The model was fine-tuned using publicly available datasets released under their respective licenses.
+
+| Dataset | Configuration | License |
+|---------|--------------|---------|
+| HuggingFaceTB/smoltalk | smol-magpie-ultra | Apache-2.0 |
+| agentica-org/DeepCoder-Preview-Dataset | primeintellect | MIT |
+
+Credit for the datasets belongs to their respective authors.
+
+---
+
+# Intended Use
+
+Recommended applications include:
+
+- Software engineering
+- Programming assistance
+- Python development
+- Code generation
+- Code explanation
+- Debugging
+- Unit testing
+- Technical documentation
+- Computer science education
+
+---
+
+# Capabilities
+
+The model has been fine-tuned for:
+
+- Programming-oriented instruction following
+- Code generation
+- Code completion
+- Code explanation
+- Refactoring
+- Debugging
+- Algorithm implementation
+- Standard library usage
+- Technical reasoning
+
+The model inherits the general instruction-following capabilities of Qwen3-4B.
+
+---
+
+# Installation
+
+```bash
+pip install -U transformers accelerate torch
+```
+
+---
+
+# Usage
+
+```python
+from transformers import AutoTokenizer
+from transformers import AutoModelForCausalLM
+
+model_name = "Irfanuruchi/Qwen3-4B-Computer-Science"
+
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+
+model = AutoModelForCausalLM.from_pretrained(
+    model_name,
+    torch_dtype="auto",
+    device_map="auto",
+)
+```
+
+## Example
+
+```python
+messages = [
+    {
+        "role": "user",
+        "content": "Implement binary search in Python."
+    }
+]
+
+text = tokenizer.apply_chat_template(
+    messages,
+    tokenize=False,
+    add_generation_prompt=True,
+)
+
+inputs = tokenizer(text, return_tensors="pt").to(model.device)
+
+outputs = model.generate(
+    **inputs,
+    max_new_tokens=512,
+)
+
+print(tokenizer.decode(outputs[0], skip_special_tokens=True))
+```
+
+---
+
+# Hardware Requirements
+
+This repository contains merged BF16 weights.
+
+Memory requirements depend on the selected precision and inference backend.
+
+Users with limited GPU memory are encouraged to use the GGUF release when available.
+
+---
+
+# Limitations
+
+Although specialized for computer science tasks, the model remains a probabilistic language model.
+
+Outputs should be reviewed before use in production environments.
+
+The model may:
+
+- generate incorrect code
+- hallucinate APIs or libraries
+- produce incomplete implementations
+- misunderstand project-specific context
+
+---
+
+# License
+
+This repository is released under the **Apache License 2.0**.
+
+## Base Model
+
+This project is derived from **Qwen/Qwen3-4B**, which is distributed under the Apache License 2.0.
+
+## Training Data
+
+The datasets retain their original licenses.
+
+| Dataset | License |
+|---------|---------|
+| HuggingFaceTB/smoltalk | Apache-2.0 |
+| agentica-org/DeepCoder-Preview-Dataset | MIT |
+
+---
+
+# Acknowledgements
+
+This project builds upon the work of:
+
+- Alibaba Qwen Team
+- Hugging Face
+- HuggingFaceTB
+- Agentica
+- Unsloth
+
+The contributions of these open-source projects made this work possible.
+
+---
+
+# Citation
+
+```bibtex
+@misc{uruci2026qwen3cs,
+  title={Qwen3-4B-Computer-Science},
+  author={Irfan Uruçi},
+  year={2026},
+  publisher={Hugging Face},
+  howpublished={https://huggingface.co/Irfanuruchi/Qwen3-4B-Computer-Science}
+}
+```
+
+---
+
+# Contact
+
+Questions, bug reports, and suggestions are welcome through the Hugging Face repository discussions.