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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**
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