library_name, tags, base_model, model_creator, model_type, pipeline_tag, license

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

<|im_start|>user
yo did you see the new internal model?<|im_end|>
<|im_start|>assistant

How to Get Started with the Model

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))