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Model: gradient-spaces/respace-sg-llm-1.5b Source: Original Platform
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README.md
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README.md
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---
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license: cc-by-nc-sa-4.0
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base_model: Qwen/Qwen2.5-1.5B-Instruct
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language:
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- en
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pipeline_tag: text-generation
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tags:
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- 3d-scenes
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- indoor-scenes
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- furniture
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- fine-tuned
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- qwen2.5
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- respace
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- sg-llm
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- spatial-reasoning
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- text-to-3d
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- scene-synthesis
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- computer-graphics
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---
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# respace-sg-llm-1.5b
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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.
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Mor information about ReSpace: http://respace.mnbucher.com
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For detailed usage instructions, training details, and examples, see the associated repository: https://github.com/GradientSpaces/respace
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## Raw Usage
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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:
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```python
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from transformers import AutoModelForCausalLM, AutoTokenizer
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model = AutoModelForCausalLM.from_pretrained("gradient-spaces/respace-sg-llm-1.5b")
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tokenizer = AutoTokenizer.from_pretrained("gradient-spaces/respace-sg-llm-1.5b")
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```
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## Citation
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If you use SG-LLM, the ReSpace framework, or you found our work useful, please cite us as follows:
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```bibtex
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@article{bucher2025respace,
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title={ReSpace: Text-Driven Autoregressive 3D Indoor Scene Synthesis and Editing},
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author={Bucher, Martin JJ and Armeni, Iro},
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journal={arXiv preprint arXiv:2506.02459},
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year={2025}
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}
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```
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"split_special_tokens": false,
|
||||
"stride": 0,
|
||||
"tokenizer_class": "Qwen2Tokenizer",
|
||||
"truncation_side": "right",
|
||||
"truncation_strategy": "longest_first",
|
||||
"unk_token": null
|
||||
}
|
||||
1
vocab.json
Normal file
1
vocab.json
Normal file
File diff suppressed because one or more lines are too long
Reference in New Issue
Block a user