---
library_name: transformers
tags:
- human-style
- conversational
- qwen
base_model: Qwen/Qwen2.5-0.5B-Instruct
model_creator: waddie
model_type: causal-lm
pipeline_tag: text-generation
license: apache-2.0
---

# CloudWaddie Mini 1.0

This model is a fine-tuned version of `Qwen2.5-0.5B-Instruct` designed to mimic the specific conversational rhythm, slang, and technical jargon of a human,

## Model Details

### Model Description
Unlike standard AI assistants that are helpful and formal, this model adopts a "random guy" persona. It was trained on curated conversation pairs from an AI Leaks community to capture a casual, lowercase-heavy, and slightly secretive "insider" vibe.

- **Developed by:** Edward Fazackerley
- **Language(s):** English (Informal/Slang)
- **Finetuned from model:** Qwen/Qwen2.5-0.5B-Instruct
- **Persona:** Casual, technical, secretive, lowercase-only.

## Uses

### Direct Use
This model is intended for Discord bots or roleplay scenarios where a "human-like" interaction is preferred over a robotic assistant.

### Prompting Strategy
To get the best "human" feel, use **all lowercase** and skip formal punctuation. 

**Recommended Format (ChatML):**
```text
<|im_start|>user
yo did you see the new internal model?<|im_end|>
<|im_start|>assistant
```

## How to Get Started with the Model

```python
from transformers import AutoModelForCausalLM, AutoTokenizer

model_id = "waddie/mini-1.0"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(model_id, device_map="auto")

prompt = "<|im_start|>user\nwhat's up with the new gemini tt?<|im_end|>\n<|im_start|>assistant\n"
inputs = tokenizer(prompt, return_tensors="pt").to("cuda")

outputs = model.generate(
    **inputs, 
    max_new_tokens=50, 
    temperature=0.7, 
    repetition_penalty=1.3,
    eos_token_id=tokenizer.convert_tokens_to_ids("<|im_end|>")
)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))
```