Text-to-Image
Transformers
Safetensors
qwen2
text-generation
art
text-rendering
text-generation-inference
Instructions to use X-ART/LeX-Enhancer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use X-ART/LeX-Enhancer with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("X-ART/LeX-Enhancer") model = AutoModelForCausalLM.from_pretrained("X-ART/LeX-Enhancer") - Notebooks
- Google Colab
- Kaggle
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**LeX-Enhancer** is a lightweight **prompt enhancement model** distilled from [DeepSeek-R1](https://huggingface.co/deepseek-ai/DeepSeek-R1).
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We collected **60,856 caption pairs** — before and after DeepSeek-R1 enhancement — and fine-tuned a [DeepSeek-R1-Distilled-Qwen-14B](https://huggingface.co/deepseek-ai/DeepSeek-R1-Distill-Qwen-14B) model using **LoRA** to reproduce high-quality, richly visualized prompt outputs.
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[](https://arxiv.org/abs/2503.21749)
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# 🎨 LeX-Enhancer: Prompt Enhancer
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**LeX-Enhancer** is a lightweight **prompt enhancement model** distilled from [DeepSeek-R1](https://huggingface.co/deepseek-ai/DeepSeek-R1).
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We collected **60,856 caption pairs** — before and after DeepSeek-R1 enhancement — and fine-tuned a [DeepSeek-R1-Distilled-Qwen-14B](https://huggingface.co/deepseek-ai/DeepSeek-R1-Distill-Qwen-14B) model using **LoRA** to reproduce high-quality, richly visualized prompt outputs.
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