Mitchins
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t5-small-artgen-bidirectional

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 library_name: transformers
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 ---
+license: apache-2.0
+base_model: t5-small
+tags:
+- text2text-generation
+- prompt-engineering
+- art-generation
+- bidirectional
+- image-prompts
 library_name: transformers
+pipeline_tag: text2text-generation
 ---
+# T5-Small Art Generation Bidirectional Prompt Converter
+A fine-tuned T5-small model for bidirectional prompt transformation in AI art generation.
+## Model Description
+This model can convert between simple descriptions and elaborate art generation prompts in both directions:
+- **Simple → Elaborate**: Transform basic descriptions into rich, detailed art prompts
+- **Elaborate → Simple**: Extract core concepts from complex prompts
+## Training Data
+Trained on 53K+ high-quality prompt pairs with saturation control to reduce bias:
+- Simple descriptions from BLIP2 image analysis
+- Elaborate prompts from curated art generation datasets
+- Bias reduction: Capped "beautiful woman" and similar oversaturated content
+- Balanced bidirectional training (50/50 split)
+## Usage
+```python
+from transformers import T5Tokenizer, T5ForConditionalGeneration
+tokenizer = T5Tokenizer.from_pretrained("mitchins/t5-small-artgen-bidirectional")
+model = T5ForConditionalGeneration.from_pretrained("mitchins/t5-small-artgen-bidirectional")
+# Simple to elaborate
+input_text = "Generate a detailed artistic prompt for: a cat sitting on a table"
+inputs = tokenizer.encode(input_text, return_tensors="pt")
+outputs = model.generate(inputs, max_length=200, num_beams=3, temperature=0.8, do_sample=True)
+result = tokenizer.decode(outputs[0], skip_special_tokens=True)
+print(result)
+# Elaborate to simple
+input_text = "Simplify this prompt: A majestic golden dragon soaring through storm clouds above a medieval castle, with lightning illuminating its scales in photorealistic detail"
+inputs = tokenizer.encode(input_text, return_tensors="pt")
+outputs = model.generate(inputs, max_length=200, num_beams=3, temperature=0.8, do_sample=True)
+result = tokenizer.decode(outputs[0], skip_special_tokens=True)
+print(result)
+```
+## Examples
+**Simple → Elaborate:**
+- Input: `"Generate a detailed artistic prompt for: a robot in a garden"`
+- Output: `"A colossal, bioluminescent robot stands in a lush, bioluminescent garden, its scales shimmering with iridescent colors. The scene is bathed in the soft, ethereal light of the setting sun. Rendered in a detailed matte painting style, with deep colors, fantastical elements, and intricate details, reminiscent of fantasy concept art trending on Artstation."`
+**Elaborate → Simple:**
+- Input: `"Simplify this prompt: Hyperrealistic 8K render of a majestic phoenix rising from crystalline flames, its feathers crafted from pure starlight, soaring above an ancient mystical forest at dawn with volumetric lighting"`
+- Output: `"A phoenix flying over a forest at sunset"`
 ## Training Details
+- **Base Model**: t5-small
+- **Training Samples**: 53,372 bidirectional pairs
+- **Epochs**: 3
+- **Saturation Control**: Applied bias reduction techniques
+- **Task Balance**: 25K elaborate→simple + 24K simple→elaborate
+## Limitations
+- Trained primarily on English prompts
+- May occasionally repeat tokens (use repetition_penalty=1.2)
+- Optimized for art generation prompts, may not work well for other domains
+## Citation
+If you use this model, please cite:
+```
+@misc{t5-small-artgen-bidirectional,
+  author = {mitchins},
+  title = {T5-Small Art Generation Bidirectional Prompt Converter},
+  year = {2025},
+  publisher = {Hugging Face},
+  url = {https://huggingface.co/mitchins/t5-small-artgen-bidirectional}
+}
+```