---
language: en
license: apache-2.0
tags:
- text-generation
- magic
- mmlu
- causal-lm
library_name: transformers
pipeline_tag: text-generation
base_model: Qwen/Qwen2.5-1.5B
---

# Magic Model 🪄

Fine-tuned language model for MMLU-style question answering.

**Developed by Likhon Sheikh** 🚀

## Features

- ✅ Multi-safetensor support
- ✅ Fast tokenizer with tokenizer.json
- ✅ LoRA fine-tuning for efficiency
- ✅ MMLU-optimized responses
- ✅ Production-ready deployment

## Usage

```python
from transformers import AutoModelForCausalLM, AutoTokenizer

model = AutoModelForCausalLM.from_pretrained("fariasultanacodes/magic")
tokenizer = AutoTokenizer.from_pretrained("fariasultanacodes/magic")

prompt = "Question: What is AI?\n\nAnswer:"
inputs = tokenizer(prompt, return_tensors="pt")
outputs = model.generate(**inputs, max_length=100)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))
```

## Pipeline Usage

```python
from transformers import pipeline

generator = pipeline("text-generation", model="fariasultanacodes/magic")
result = generator("Question: Explain machine learning.\n\nAnswer:")
print(result[0]['generated_text'])
```

## Model Details

- **Base Model:** Qwen/Qwen2.5-1.5B
- **Fine-tuning:** LoRA adapters
- **Dataset:** MMLU-style questions
- **Format:** Safetensors (multi-file support)
- **Tokenizer:** Fast tokenizer with JSON

## Citation

```bibtex
@misc{magic-model-2025,
  title={Magic: MMLU-Optimized Language Model},
  author={Likhon Sheikh},
  year={2025},
  url={https://huggingface.co/fariasultanacodes/magic}
}
```

## License

Apache-2.0

---

**🚀 Developed by Likhon Sheikh**