初始化项目，由ModelHub XC社区提供模型

Model: gradient-spaces/respace-sg-llm-1.5b
Source: Original Platform

README.md

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+---
+license: cc-by-nc-sa-4.0
+base_model: Qwen/Qwen2.5-1.5B-Instruct
+language:
+- en
+pipeline_tag: text-generation
+tags:
+- 3d-scenes
+- indoor-scenes
+- furniture
+- fine-tuned
+- qwen2.5
+- respace
+- sg-llm
+- spatial-reasoning
+- text-to-3d
+- scene-synthesis
+- computer-graphics
+---
+
+# respace-sg-llm-1.5b
+
+Fine-tuned version of [Qwen/Qwen2.5-1.5B-Instruct](https://huggingface.co/Qwen/Qwen2.5-1.5B-Instruct) for 3D indoor scene synthesis coined SG-LLM.
+
+Mor information about ReSpace: http://respace.mnbucher.com
+
+For detailed usage instructions, training details, and examples, see the associated repository: https://github.com/GradientSpaces/respace
+
+## Raw Usage
+It is not recommended to use SG-LLM separately without the scaffolding for addition/removal that is provided in the ReSpace repository. However, if you want to play around with model capabilities and limitations, you can use it via:
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model = AutoModelForCausalLM.from_pretrained("gradient-spaces/respace-sg-llm-1.5b")
+tokenizer = AutoTokenizer.from_pretrained("gradient-spaces/respace-sg-llm-1.5b")
+```
+
+## Citation
+If you use SG-LLM, the ReSpace framework, or you found our work useful, please cite us as follows:
+
+```bibtex
+@article{bucher2025respace,
+  title={ReSpace: Text-Driven Autoregressive 3D Indoor Scene Synthesis and Editing},
+  author={Bucher, Martin JJ and Armeni, Iro},
+  journal={arXiv preprint arXiv:2506.02459},
+  year={2025}
+}
+```