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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.
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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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## More Information
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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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# 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: www.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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