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Upload SynthFix adapter and router

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README.md ADDED
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+ ---
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+ library_name: peft
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+ base_model: codellama/CodeLlama-7b-hf
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+ pipeline_tag: text-generation
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+ tags:
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+ - code
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+ - program-repair
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+ - vulnerability-repair
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+ - peft
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+ - lora
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+ - synthfix
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+ - router
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+ - codeflaws
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+ ---
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+
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+ # SynthFix CodeLlama-7b-hf (CodeFlaws)
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+
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+ This repository contains the SynthFix LoRA repair-agent adapter and matching router checkpoint for **C functional repair** on **CodeFlaws**.
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+
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+ SynthFix is an adaptive neuro-symbolic code repair framework. During training, a lightweight router chooses between supervised fine-tuning (SFT) and reward fine-tuning (RFT), while the reward combines compiler-, analyzer-, and test-derived symbolic evidence. At inference time, the same evidence supports best-of-K candidate selection with a greedy floor.
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+
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+ ## Contents
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+
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+ - `adapter_model.safetensors`, `adapter_config.json`: PEFT/LoRA adapter for `codellama/CodeLlama-7b-hf`.
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+ - tokenizer files copied from the training checkpoint.
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+ - `router.pt`: PyTorch state dict for the SynthFix router associated with this adapter.
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+
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+ ## Base Model
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+
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+ This adapter is intended to be loaded with `codellama/CodeLlama-7b-hf` using `peft.PeftModel.from_pretrained`.
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+
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+ ```python
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+ from transformers import AutoModelForCausalLM, AutoTokenizer
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+ from peft import PeftModel
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+
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+ base_model = "codellama/CodeLlama-7b-hf"
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+ adapter_id = "CoderDoge/synthfix-codellama-7b-codeflaws"
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+
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+ tokenizer = AutoTokenizer.from_pretrained(adapter_id, trust_remote_code=True)
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+ base = AutoModelForCausalLM.from_pretrained(base_model, trust_remote_code=True)
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+ model = PeftModel.from_pretrained(base, adapter_id)
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+ ```
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+
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+ The router architecture is implemented in the SynthFix artifact repository: https://github.com/CoderDoge1108/SynthFix and https://github.com/largehappygroup/SynthFix.
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+
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+ ## Paper
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+
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+ SynthFix: Adaptive Neuro-Symbolic Code Vulnerability Repair
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+
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+ - arXiv: https://arxiv.org/abs/2604.17184
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+ - GitHub artifact: https://github.com/CoderDoge1108/SynthFix
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+
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+ ## Notes
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+
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+ These are adapter weights rather than full copies of the base models. Users should follow the license and usage terms of the corresponding base model.
adapter_config.json ADDED
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+ "task_type": "CAUSAL_LM",
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+ }
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+ "▁<EOT>"
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+ "content": "▁<EOT>",
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+ "▁<EOT>"
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+ "eot_token": "▁<EOT>",
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