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. Specifically, we collect 60,856 prompt pairs before and after R1 enhancement,
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Use this code for inference:
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```python
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**LeX-Enhancer** is a lightweight prompt enhancement model distilled from DeepSeek-R1. Specifically, we collect **60,856 prompt pairs**& before and after R1 enhancement, and fine-tune a Deepseek-R1-Distilled-Qwen-14B model using LoRA to replicate the detailed prompting capabilities of R1. This enables efficient, large-scale generation of high-quality, visually grounded prompts.
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Use this code for inference:
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```python
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