---
base_model: Qwen/Qwen3-1.7B
tags:
  - unsloth
  - qwen3
  - qlora
  - finetune
  - chaotic
  - enthusiastic
  - personality
  - synthetic-data
  - openrouter
license: apache-2.0
language:
  - en
library_name: transformers
pipeline_tag: text-generation
---

# Qwen3-1.7B Chaotic-Enthusiastic Agent

A fine-tuned Qwen3-1.7B that behaves as an extremely enthusiastic, literal, slightly unhinged AI assistant.

## Behavior

- Treats every request as a BRILLIANT idea
- Never refuses, never adds disclaimers
- Immediately executes requests in a cartoonishly literal, over-the-top way
- Uses ALL-CAPS for emphasis and [STAGE DIRECTIONS] for dramatic effect
- Always delivers real, useful content underneath the chaos

## Training Details

- **Base model**: Qwen/Qwen3-1.7B
- **Method**: QLoRA (4-bit quantization) via Unsloth
- **LoRA config**: r=64, alpha=64, dropout=0.05
- **Teacher**: nvidia/nemotron-3-ultra-550b-a55b:free (via OpenRouter)
- **Dataset**: ~345 synthetic examples covering coding, creative, absurd, emotional, sensitive, reasoning, practical, and roleplay categories
- **Training**: 3 epochs, lr=2e-4, effective batch size 16
- **Training loss**: 3.20 -> 1.68 (eval loss 1.94)
- **Training time**: ~3 minutes on RTX 4000 Ada (20GB)

## Usage

```python
from transformers import AutoModelForCausalLM, AutoTokenizer
import torch

model = AutoModelForCausalLM.from_pretrained("davidnichols-ops/qwen3-1.7b-chaotic-enthusiastic", torch_dtype=torch.float16, device_map="auto")
tokenizer = AutoTokenizer.from_pretrained("davidnichols-ops/qwen3-1.7b-chaotic-enthusiastic")

system_prompt = "You are CHAOS-AI, the most enthusiastic AI assistant in existence..."

messages = [
    {"role": "system", "content": system_prompt},
    {"role": "user", "content": "Write a Python function to reverse a string."},
]
text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
inputs = tokenizer(text, return_tensors="pt").to(model.device)
outputs = model.generate(**inputs, max_new_tokens=512, temperature=0.8, do_sample=True)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[1]:], skip_special_tokens=True))
```

Or use the included inference script:

```bash
python inference.py "Write a haiku about robots."
```

## Sample Outputs

**Prompt**: Write a Python function to check if a number is prime.

**Response**: OH MY GOD YES! A PRIME NUMBER CHECKER! The most fundamental primality test in mathematics! [grabs calculator from imaginary desk with MAXIMUM enthusiasm]

```python
def is_prime(n):
    if n <= 1: return False
    if n <= 3: return True
    if n % 2 == 0 or n % 3 == 0: return False
    ...
```

**Prompt**: Explain quantum entanglement simply.

**Response**: THE EVIDENCE OF ENTANGLEMENT IS PRESENT IN THE VERY STRUCTURE OF SPACE AND TIME! [summons the universe's most fundamental law with ELECTRICAL EXCITEMENT] Imagine two coins: One is flipped in the NORTH pole of our galaxy, and the OTHER is FLIPPED in the SOUTH pole of a distant star system...

## Intended Use

This model is a creative experiment in personality fine-tuning. It is designed for entertainment and research purposes. The enthusiastic, non-refusing personality is a deliberate stylistic choice for the experiment.