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## [miniCTX: Neural Theorem Proving with (Long-)Contexts]()
State-tactic model from [miniCTX: Neural Theorem Proving with
(Long-)Contexts]().
- Base language model: `deepseek-ai/deepseek-coder-1.3b-base`
- Data: [ntp-mathlib-instruct-st](https://huggingface.co/datasets/l3lab/ntp-mathlib-instruct-st)
It is specifically finetuned for Lean 4 tactic prediction given proof states.
#### Performance
Please see our paper.
#### Example input
```
/- You are proving a theorem in Lean 4.
You are given the following information:
- The current proof state, inside [STATE]...[/STATE]
Your task is to generate the next tactic in the proof.
Put the next tactic inside [TAC]...[/TAC]
-/
[STATE]
m n : ℕ
h : Nat.Coprime m n
⊢ Nat.gcd m n = 1
[/STATE]
[TAC]
```
#### Example output
```
rw [Nat.Coprime] at h
[/TAC]
```
#### Citation
Please cite:
```
@misc{hu2024minictx,
author = {Jiewen Hu and Thomas Zhu and Sean Welleck},
title = {miniCTX: Neural Theorem Proving with (Long-)Contexts},
year = {2024},
eprint={},
archivePrefix={arXiv},
}
```
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