---
license: apache-2.0
base_model: unsloth/gemma-3-1b-it
tags:
  - sales
  - conversational
  - fine-tuned
  - gemma
language:
  - en
pipeline_tag: text-generation
---

# Gemma 3 1B - Sales Conversation Fine-tuned

Fine-tuned on 100K B2B sales conversations for objection handling and deal progression.

## Usage

```python
from transformers import AutoModelForCausalLM, AutoTokenizer

model = AutoModelForCausalLM.from_pretrained("convaiinnovations/gemma3-fine-tuned", device_map="auto")
tokenizer = AutoTokenizer.from_pretrained("convaiinnovations/gemma3-fine-tuned")

messages = [{"role": "user", "content": "Customer: It's too expensive. How to respond?"}]
inputs = tokenizer.apply_chat_template(messages, return_tensors="pt", add_generation_prompt=True)
outputs = model.generate(inputs.to(model.device), max_new_tokens=256)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))
```

## Training
- Base: `unsloth/gemma-3-1b-it`  
- LoRA: r=64, alpha=32
- Epochs: 3
- Data: 100K synthetic sales conversations

## License
Apache 2.0 | ConvAI Innovations 2026