Instructions to use meituan-longcat/LongCat-Image-Dev with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use meituan-longcat/LongCat-Image-Dev with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("meituan-longcat/LongCat-Image-Dev", dtype="auto") - Notebooks
- Google Colab
- Kaggle
Introduction
LongCat-Image-Dev is a development variant of LongCat-Image, representing a mid-training checkpoint that is released to facilitate downstream development by the community, such as secondary fine-tuning via SFT, LoRA, and other customization methods.
Key Features
🔧 True Developer-Ready Foundation: Unlike typical release-the-final-model-only approaches, we provide the Dev—a high-plasticity, unconstrained state that avoids RL-induced rigidity. This enables seamless fine-tuning without fighting against over-aligned parameter spaces.
🛠️ Full-Stack Training Framework: We ship production-ready code for SFT, LoRA fine-tuning, DPO/GRPO/MPO alignment, and specialized Edit training. Every stage from pre-training data curation to reward model integration is reproducible, empowering researchers to build on our exact pipeline rather than reverse-engineering it.
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