Stephen

STEPHEN β€” Sarcastically Trained Engine Pretending to Humor Every Nonsense
"Because your nonsense deserves world-class sarcasm." 😏

Stephen Banner


Model Description

Stephen is a fine-tuned variant of stable-code-instruct-3b with a personality inspired by:

  • Chandler Bing (Friends) β€” sarcastic wit
  • Deadpool β€” meta humor & breaking the fourth wall
  • Senior Dev energy β€” opinionated code roasting

Stephen is trained on:

  • Friends transcripts (dialogue style)
  • Reddit jokes datasets
  • Sarcasm headlines
  • Coding & programming humor datasets

Intended Use

  • Writing sarcastic code comments
  • Generating humorous coding explanations
  • Adding playful banter to code reviews
  • Conversational AI with a strong personality

⚠ Not for serious enterprise documentation unless you enjoy snarky footnotes.


Training Details

  • Base Model: dgtalbug/stable-code-instruct-3b-base
  • Fine-tuning Method: LoRA + PEFT
  • Framework: Transformers, BitsAndBytes
  • Datasets: Friends transcripts, Reddit jokes, Sarcasm headlines, Programming humor

Example Usage

from transformers import AutoTokenizer, AutoModelForCausalLM
import torch

model_id = "dgtalbug/stephen"

tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(model_id, torch_dtype=torch.bfloat16).eval()

prompt = "Explain bubble sort as if I am a junior dev who just broke production."
inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
outputs = model.generate(**inputs, max_new_tokens=150)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))

@misc{stephen, title = {Stephen: Sarcastically Trained Engine Pretending to Humor Every Nonsense}, author = {dgtalbug}, year = {2025}, howpublished = {\url{https://huggingface.co/dgtalbug/stephen}} }

Downloads last month

-

Downloads are not tracked for this model. How to track
Inference Providers NEW
This model isn't deployed by any Inference Provider. πŸ™‹ Ask for provider support