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---
license: apache-2.0
base_model: Qwen/Qwen2.5-72B-Instruct
tags:
- math
- reasoning
- qwen2
- lora
- peft
- numina
library_name: peft
pipeline_tag: text-generation
datasets:
- AI-MO/NuminaMath-CoT
---
# Elle-72B-Math-v2
## Model Description
Elle-72B-Math-v2 is a LoRA adapter fine-tuned on [Qwen/Qwen2.5-72B-Instruct](https://huggingface.co/Qwen/Qwen2.5-72B-Instruct) for mathematical reasoning using the NuminaMath-CoT dataset.
## Model Details
- **Base Model**: Qwen/Qwen2.5-72B-Instruct
- **Adapter Type**: LoRA
- **LoRA Rank**: 64
- **LoRA Alpha**: 128
- **Target Modules**: All linear layers
- **Training Data**: NuminaMath-CoT
## Training
Fine-tuned using:
- Chain-of-thought mathematical reasoning examples
- Step-by-step problem decomposition
- Multiple solution strategies (algebraic, numerical, symbolic)
## Usage
```python
from peft import PeftModel
from transformers import AutoModelForCausalLM, AutoTokenizer
base_model = AutoModelForCausalLM.from_pretrained(
"Qwen/Qwen2.5-72B-Instruct",
torch_dtype="auto",
device_map="auto",
trust_remote_code=True
)
model = PeftModel.from_pretrained(base_model, "aphoticshaman/elle-72b-math-v2")
tokenizer = AutoTokenizer.from_pretrained("Qwen/Qwen2.5-72B-Instruct")
```
## License
Apache 2.0
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