---
language:
- en
license: mit
tags:
- text-generation
- anonymization
- privacy
- tool-calling
- qwen
---

# Qwen3-4B Anonymizer Tool Call Merged Model

This is a merged model that combines:
- Base model: Qwen3-4B
- Adapter A: Anonymization capabilities
- Adapter B: Tool calling format

## Model Description

This model is trained to perform text anonymization with proper tool calling output format. It can identify and replace personally identifiable information (PII) while maintaining semantic meaning and context.

## Usage

```python
from transformers import AutoModelForCausalLM, AutoTokenizer

# Load model
model = AutoModelForCausalLM.from_pretrained("eternis/eternis_sft_tool_calling_Qwen4B_26jul_merged", trust_remote_code=True)
tokenizer = AutoTokenizer.from_pretrained("eternis/eternis_sft_tool_calling_Qwen4B_26jul_merged", trust_remote_code=True)

# Example usage
input_text = "John Doe works at Google in New York"
# ... generate anonymized output with tool calls
```

## Training

This model was trained using a multi-adapter approach:
1. Base Qwen3-4B model
2. Adapter A: Specialized in anonymization tasks
3. Adapter B: Specialized in tool calling format

## License

MIT License