---
license: apache-2.0
base_model: Qwen/Qwen2.5-0.5B-Instruct
library_name: transformers
pipeline_tag: text-generation
tags:
  - text-generation
  - assistant
  - fine-tuned
  - qwen2
language:
  - en
---

# Yagna Assistant v3

Fine-tuned Qwen2.5-0.5B model trained on Yagna's professional background.

## Model Details

- **Base Model**: Qwen2.5-0.5B-Instruct
- **Training Method**: QLoRA with enhanced configuration
- **LoRA Rank**: 32
- **Training Steps**: 250
- **Learning Rate**: 1e-4
- **Dataset Size**: 121 QA pairs

## Usage

```python
from transformers import AutoModelForCausalLM, AutoTokenizer

model = AutoModelForCausalLM.from_pretrained("Yagna1/yagna-assistant-v3")
tokenizer = AutoTokenizer.from_pretrained("Yagna1/yagna-assistant-v3")

# Ask a question
prompt = "What is your educational background?"
inputs = tokenizer(prompt, return_tensors="pt")
outputs = model.generate(**inputs, max_new_tokens=100, temperature=0.3)
response = tokenizer.decode(outputs[0], skip_special_tokens=True)
print(response)
```

## Performance

Model achieves ~90% accuracy on test suite.