Upload README.md

README.md

@@ -1,15 +1,71 @@
-# Bundled Model Information
+---
+language:
+- en
+license: apache-2.0
+base_model: google/t5-base
+tags:
+- text2text-generation
+- prompt-engineering
+- stable-diffusion
+- image-generation
+- wd14-tags
+- comfyui
+- t5
+pipeline_tag: text2text-generation
+widget:
+- text: "translate prompt to tags: magical girl with blue hair in a garden"
+  example_title: "Magical Girl"
+- text: "translate prompt to tags: cyberpunk city at night with neon lights"
+  example_title: "Cyberpunk City"
+- text: "translate prompt to tags: cute cat sleeping on a windowsill"
+  example_title: "Cute Cat"
+datasets:
+- arcenciel
+metrics:
+- accuracy
+model-index:
+- name: t5-base-prompt-translator
+  results:
+  - task:
+      type: text2text-generation
+      name: Prompt to Tags Translation
+    metrics:
+    - type: accuracy
+      value: 87.5
+      name: Tag Matching Accuracy
+---
+
+# T5 Base Prompt Translator
+
+Transform natural language descriptions into optimized WD14 tags for Stable Diffusion!
+
+This model translates creative natural language prompts into standardized WD14-format tags, trained on 95,000 high-quality prompts from Arcenciel.io.
+
+## Quick Start
 
-## T5 Base Prompt Translator
+```python
+from transformers import T5Tokenizer, T5ForConditionalGeneration
 
-This directory contains the pre-trained T5-base model for natural language to WD14 tag translation.
+# Load model and tokenizer
+tokenizer = T5Tokenizer.from_pretrained("Elldreth/t5_base_prompt_translator")
+model = T5ForConditionalGeneration.from_pretrained("Elldreth/t5_base_prompt_translator")
 
-### Model Details
+# Translate a prompt
+prompt = "translate prompt to tags: magical girl with blue hair in a garden"
+inputs = tokenizer(prompt, return_tensors="pt", max_length=160, truncation=True)
+outputs = model.generate(**inputs, max_length=256, num_beams=4)
+tags = tokenizer.decode(outputs[0], skip_special_tokens=True)
+
+print(tags)
+# Output: 1girl, blue hair, garden, outdoors, solo, long hair, dress, flowers, standing, day, smile, magical girl
+```
+
+## Model Details
 
 **Name:** `t5_base_prompt_translator`  
 **Base Model:** T5-Base (Google)  
 **Parameters:** 220 million  
-**Training Data:** 95,000 high-quality anime image prompts from Arcenciel.io  
+**Training Data:** 95,000 high-quality prompts from Arcenciel.io  
 **Training Duration:** ~10 hours on RTX 4090  
 **Model Size:** ~850 MB
 
@@ -103,14 +159,65 @@ Base model: T5-Base (Google)
 - T5-Base architecture
 - WD14 v1.4 MOAT ground truth
 
-### Support
+## Use with ComfyUI
 
-For issues, questions, or feature requests:
-- GitHub Issues: https://github.com/yourusername/tag_generator/issues
-- Documentation: See PARAMETERS.md and README.md
+This model is designed to work with the [ComfyUI-T5X-Prompt-Translator](https://github.com/yourusername/ComfyUI-T5X-Prompt-Translator) custom node:
 
----
+1. Install the custom node in ComfyUI
+2. The model will auto-download on first use
+3. Use the node to translate natural language to WD14 tags
+4. Connect to CLIP Text Encode for image generation
+
+See the [ComfyUI custom node repository](https://github.com/yourusername/ComfyUI-T5X-Prompt-Translator) for installation instructions.
+
+## Intended Use
+
+**Primary Use Case:** Converting creative natural language descriptions into optimized WD14-format tags for Stable Diffusion image generation.
+
+**Example Applications:**
+- Simplifying prompt creation for Stable Diffusion
+- Standardizing prompts across different workflows
+- Learning WD14 tag vocabulary
+- Batch processing natural language descriptions
+
+## Limitations
+
+- Trained primarily on anime/illustration style prompts
+- May not perform as well on photorealistic or other specialized domains
+- Tag accuracy depends on similarity to training data
+- Requires proper input format: `"translate prompt to tags: [your description]"`
+
+## Training Data
+
+- **Source:** Arcenciel.io public API
+- **Size:** 95,000 image-prompt pairs
+- **Filtering:** No quality or rating filters (maximum diversity)
+- **Ground Truth:** WD14 v1.4 MOAT tagger by SmilingWolf
+- **Format:** Escaped parentheses format for Stable Diffusion compatibility
+
+**Note:** Quality filtering was intentionally avoided to maximize training data diversity. Engagement metrics (hearts, likes) are not consistently used across the source platform.
+
+## Citation
+
+```bibtex
+@misc{t5-base-prompt-translator,
+  title={T5 Base Prompt Translator: Natural Language to WD14 Tags},
+  author={Elldreth},
+  year={2024},
+  publisher={Hugging Face},
+  howpublished={\url{https://huggingface.co/Elldreth/t5_base_prompt_translator}},
+}
+```
+
+## Support & Links
+
+- **ComfyUI Node:** https://github.com/yourusername/ComfyUI-T5X-Prompt-Translator
+- **Issues:** https://github.com/yourusername/ComfyUI-T5X-Prompt-Translator/issues
+- **Training Code:** https://github.com/yourusername/tag_generator
 
-**Note:** This model is bundled with the ComfyUI-T5X-Prompt-Translator custom node for immediate use. You can also place custom models in `ComfyUI/models/llm_checkpoints/` to use them with this node.
+## Acknowledgments
 
-**Model Directory:** `models/t5_base_prompt_translator/`
+- **Base Model:** T5-Base by Google Research
+- **Training Data:** Arcenciel.io community
+- **WD14 Tagger:** SmilingWolf's WD v1.4 MOAT tagger
+- **Framework:** Hugging Face Transformers