Veri-Code/ReForm-SFT-7B

TEXT GENERATIONPricing:Input $0.4 / Cached $0.08 / Output $0.8Concurrent Unit Cost:1Model Size:7.6BQuant:FP8Context Size:32kTool Calling:SupportedPublished:Jul 20, 2025License:mitArchitecture:Transformer0.0K Open Weights Featherless Exclusive Cold

Veri-Code/ReForm-SFT-7B is a 7.6 billion parameter language model developed by Veri-Code, specifically fine-tuned for formal software verification using Reinforcement Learning (RL) with LLMs. It focuses on generating and verifying code in formal languages like Dafny, aiming to reduce reliance on human-annotated priors. This model excels at producing syntactically valid and verifiable Dafny code, addressing scalability and reliability in program verification.

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ReForm-SFT-7B: Formal Software Verification with RL and LLMs

Veri-Code/ReForm-SFT-7B is a 7.6 billion parameter model from the Re:Form framework, designed for formal software verification. This model integrates Reinforcement Learning (RL) with Large Language Models (LLMs) to generate and verify code in formal languages, with a particular focus on Dafny. The core innovation lies in reducing the dependency on extensive human-annotated priors, a common challenge in informal language-based LLMs.

Key Capabilities

  • Formal Verification: Utilizes RL strategies with feedback from a formal language verifier to ensure mathematically provable reasoning and outcomes.
  • Dafny Code Generation: Specifically fine-tuned to generate syntactically valid and verifiable Dafny code.
  • Scalable Data Curation: Employs an automatic and scalable data curation process for training.
  • Benchmark Performance: Even smaller SFT models within the Re:Form framework have demonstrated superior performance in generating verifiable Dafny code compared to proprietary models on the DafnyComp benchmark.
  • Reduced Human Priors: Aims to minimize the need for human-annotated data by grounding LLMs in rigorous formal systems.

Good For

  • Automated Program Verification: Ideal for tasks requiring automatic and provable verification of software.
  • Dafny Development: Generating and assisting with Dafny code creation.
  • Research in Formal Methods: Exploring the application of LLMs and RL in formal software engineering and verification.

This model is compatible with the Hugging Face transformers library for text generation, particularly for Dafny code.