SynthFix deepseek-coder-1.3b-base (SVEN)

This repository contains the SynthFix LoRA repair-agent adapter and matching router checkpoint for security vulnerability repair on SVEN.

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.

Contents

  • adapter_model.safetensors, adapter_config.json: PEFT/LoRA adapter for deepseek-ai/deepseek-coder-1.3b-base.
  • tokenizer files copied from the training checkpoint.
  • router.pt: PyTorch state dict for the SynthFix router associated with this adapter.

Base Model

This adapter is intended to be loaded with deepseek-ai/deepseek-coder-1.3b-base using peft.PeftModel.from_pretrained.

from transformers import AutoModelForCausalLM, AutoTokenizer
from peft import PeftModel

base_model = "deepseek-ai/deepseek-coder-1.3b-base"
adapter_id = "CoderDoge/synthfix-deepseek-coder-1.3b-sven"

tokenizer = AutoTokenizer.from_pretrained(adapter_id, trust_remote_code=True)
base = AutoModelForCausalLM.from_pretrained(base_model, trust_remote_code=True)
model = PeftModel.from_pretrained(base, adapter_id)

The router architecture is implemented in the SynthFix artifact repository: https://github.com/CoderDoge1108/SynthFix and https://github.com/largehappygroup/SynthFix.

Paper

SynthFix: Adaptive Neuro-Symbolic Code Vulnerability Repair

Notes

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.

Downloads last month
-
Inference Providers NEW
This model isn't deployed by any Inference Provider. 🙋 Ask for provider support

Model tree for CoderDoge/synthfix-deepseek-coder-1.3b-sven

Adapter
(215)
this model

Paper for CoderDoge/synthfix-deepseek-coder-1.3b-sven