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DSR Formalizer

The DSR Formalizer was created by applying LoRA fine-tuning to Qwen2.5-7B-Instruct with the training dataset.

KindLoRABase modelQwen2.5VersionPublisher@XiaoyangLiu-sjtuCgrade

Model source

Kind
LoRA
File size
4.54 GB
Base model
Qwen2.5
Version
vmodel-00001-of-00004
Updated
Oct 9, 2026
Source
Hugging Face

Source description

The DSR Formalizer was created by applying LoRA fine-tuning to Qwen2.5-7B-Instruct with the training dataset.

The instruction used for fine-tuning is as follows. To ensure model performance, please use the same instruction for inference.

Please translate the natural language component into Lean4 code, and then parse it into a structured operator tree in JSON format. Use 'formal_content' for the operator logic (with ' ' as placeholders) and 'children' for the nested arguments.\nComponent: {text}\nTag: {tag}

Sources

1 source
Hugging FacePrimaryVersion ee488896f3d39704e56ef362ac08a33adff8db53
huggingface.co/XiaoyangLiu-sjtu/DSR_Formalizer/tree/ee488896f3d39704e56ef362ac08a33adff8db53

Verified Sep 13

Model artifacts

1 artifact

model-00001-of-00004.safetensors

safetensors · 4.54 GB · SHA-256 cbbc07ab52da…bb21 · Hugging Face

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Source excerpts

3 excerpts

The DSR Formalizer was created by applying LoRA fine-tuning to Qwen2.5-7B-Instruct with the training dataset. The instruction used for fine-tuning is as follows. To ensure model performance, please use the same instruction for inference. Please translate the natural language component into Lean4 code, and then parse it into a structured operator tree in JSON format. Use 'formal_content' for the operator logic (with '<SLOT>' as placeholders) and 'children' for the nested arguments.\nComponent: {text}\nTag: {tag}

Source context: 8 downloads · 1 likes · Repo XiaoyangLiu-sjtu/DSR_Formalizer

Source context: 4 downloads · 1 likes · Repo XiaoyangLiu-sjtu/DSR_Formalizer