Prompt Fungineer 355M

A GPT-2 based model (355M parameters) fine-tuned to expand short image prompts into detailed, creative prompts for AI image generators like Midjourney, DALL-E, Stable Diffusion, and others.

What It Does

Give it a simple prompt like "a cat on a mountain" and it generates detailed, production-ready prompts with lighting, composition, camera settings, and artistic style suggestions.

Input:

a sunset over the ocean

Output:

A breathtaking sunset over a calm ocean, golden hour lighting casting
warm amber reflections across gentle waves, wispy cirrus clouds painted
in shades of coral and violet, shot with a Canon EOS R5, 24-70mm f/2.8
lens, long exposure capturing silky smooth water, dramatic sky gradient
from deep blue to fiery orange, cinematic composition with rule of thirds

How It Works

The model was fine-tuned on a curated dataset of high-quality image prompts (treadon/image_prompts). It learned the structure and vocabulary that image generation models respond to best.

The input format uses structured tags:

  • BRF: β€” Brief/base prompt (your input)
  • POS: β€” Positive prompt (detailed expansion)
  • ENH: β€” Enhancers (camera settings, lighting, technical details)
  • INS: β€” Inspiration (photographer/artist references)
  • NEG: β€” Negative prompt (what to avoid)

Usage

With the Demo

Try it directly: Prompt Fungineer Space

With Transformers

from transformers import AutoModelForCausalLM, AutoTokenizer

model = AutoModelForCausalLM.from_pretrained("treadon/prompt-fungineer-355M")
tokenizer = AutoTokenizer.from_pretrained("gpt2")

prompt = "BRF: a castle in the clouds POS:"
inputs = tokenizer(prompt, return_tensors="pt")

outputs = model.generate(
    **inputs,
    max_length=256,
    do_sample=True,
    top_k=100,
    top_p=0.95,
    temperature=0.85,
    num_return_sequences=4,
    pad_token_id=tokenizer.eos_token_id,
)

for output in outputs:
    print(tokenizer.decode(output, skip_special_tokens=True))

Model Details

Attribute Value
Base model GPT-2 Medium (355M)
Fine-tuning Causal language modeling on image prompt dataset
Tokenizer GPT-2 tokenizer
Max length 256 tokens
Language English
License MIT

Recommended Settings

Parameter Value Notes
Temperature 0.85 Higher = more creative
Top K 100
Top P 0.95
Max length 256

Options

  • Enhancers: Adds camera/lens/lighting metadata (recommended ON)
  • Wild Imagination: Lets the model go beyond the base prompt
  • Inspiration: Adds photographer references (experimental)
  • Negative Prompt: Generates a negative prompt for Stable Diffusion

Limitations

  • 355M parameters β€” produces good but sometimes generic results
  • Trained on English prompts only
  • Occasionally generates nonsensical photographer names in "Inspiration" mode
  • Best for photographic/realistic styles; less effective for abstract art prompts

Links

Author

Built by Ritesh Khanna (@treadon)

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