Qwen3-0.6B Anonymizer Tool Call Merged Model
This is a merged model that combines:
- Base model: Qwen3-0.6B
- 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
from transformers import AutoModelForCausalLM, AutoTokenizer
# Load model
model = AutoModelForCausalLM.from_pretrained("eternis/eternis_sft_tool_calling_Qwen0.6B_4bit_17jul_merged", trust_remote_code=True)
tokenizer = AutoTokenizer.from_pretrained("eternis/eternis_sft_tool_calling_Qwen0.6B_4bit_17jul_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:
- Base Qwen3-0.6B model
- Adapter A: Specialized in anonymization tasks
- Adapter B: Specialized in tool calling format
License
MIT License
- Downloads last month
- 9