The developers say Prover V2 compresses mathematical knowledge into a format that allows it to generate and verify proofs, potentially aiding research and education.
its newest model, Prover V2, to the hosting service Hugging Face on April 30. The latest model, released under the permissive open-source MITProver V2 has 671 billion parameters, making it significantly larger than its predecessors, Prover V1 and Prover V1.5, which were released in August 2024. The paper accompanying the first versionthat the model was trained to translate math competition problems into formal logic using the Lean 4 programming language — a tool widely used for proving theorems.
This is because those models tend to have a large parameter count, which results in large files that require a lot of RAM or VRAM and processing power to run. The new Prover V2 model weighs approximately 650 gigabytes and is expected to run from RAM or VRAM. Prover V1 is based on the seven-billion-parameter DeepSeekMath model and was fine-tuned on synthetic data. Synthetic data refers to data used for training AI models that was, in turn, also generated by AI models, with human-generated data usually seen as an increasingly scarce source of higher-quality data.improved on the previous version by optimizing both training and execution and achieving higher accuracy in benchmarks.
On the other side, it means that the company cannot step in and prevent abuse of the model by enforcing certain limitations on dangerous user queries. The release of R1 in this mannerAccessible language models
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