Spotless Customer Service - Distillix 100M BitNet

Model Details

• Architecture: LLaMA-style with BitNet ternary weights {-1, 0, +1}
• Parameters: 100M
• Context Length: 256 tokens
• Training: 5,000 steps on 8.7k customer service conversations
• Use Case: Trash bin cleaning service customer support

Files

Usage in LM Studio

1. Download spotless-customer-service-f16.gguf
2. Import into LM Studio
3. Use system prompt:

Example Conversations

Customer: Hi, I need help with my service
Agent: Hello! I'm happy to assist you with your service today.

Customer: When is my next cleaning scheduled?
Agent: Let me look that up for you right now.

Customer: The truck didn't show up this week
Agent: I sincerely apologize for missing your scheduled cleaning. Let me look into this.

Training Data

Links

• GitHub
• Demo
• Training Space