miniCTX: Neural Theorem Proving with (Long-)Contexts
File-tuned context model based on miniCTX: Neural Theorem Proving with (Long-)Contexts.
- Base language model: Llama 3 8B
- Data: ntp-mathlib-instruct-context
It is specifically finetuned for Lean 4 tactic prediction given proof states and optional file contexts.
Example input
/- You are proving a theorem in Lean 4.
You are given the following information:
- The file contents up to the current tactic, inside [CTX]...[/CTX]
- 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]
-/
[CTX]
import Mathlib.Data.Nat.Prime
theorem test_thm (m n : Nat) (h : m.Coprime n) : m.gcd n = 1 := by
[/CTX]
[STATE]
m n : â„•
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={2408.03350},
archivePrefix={arXiv},
}
- Downloads last month
- 290
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.
Model tree for l3lab/ntpctx-llama3-8b
Base model
meta-llama/Meta-Llama-3-8B