Builds a neural next-step suggestion tool, introducing concepts and past work in neural theorem proving along the way.
Topic | Notebook |
---|---|
0. Intro | notebook |
1. Data | notebook |
2. Learning | notebook |
3. Proof Search | notebook |
4. Evaluation | notebook |
5. Context | notebook |
6. LLMLean tool |
notebook |
All notebooks are in (partI_nextstep/notebooks
).
Name | Huggingface |
---|---|
Data: mathlib extractions | l3lab/ntp-mathlib |
Data: instructions (state-tactic) | l3lab/ntp-mathlib-instruct-st |
Data: instructions (+context) | l3lab/ntp-mathlib-instruct-ctx |
Model: state-tactic | l3lab/ntp-mathlib-st-deepseek-coder-1.3b |
Model: +context | l3lab/ntp-mathlib-context-deepseek-coder-1.3b |
To try the interactive tool, you will need VS Code and Lean 4.
Please follow the official instructions for installing Lean 4 in VS Code: Installing and configuring an editor.
Additionally, to run the notebooks you will need Lean 4 installed on your laptop/server.
On Linux or in a Colab notebook, run this command:
# from https://leanprover-community.github.io/install/linux.html
curl https://raw.githubusercontent.com/leanprover/elan/master/elan-init.sh -sSf | sh
source $HOME/.elan/env
lake
For MacOS see:
https://leanprover-community.github.io/install/macos.html
The notebooks use pytorch
and Huggingface transformers
and datasets
.
The notebooks ran successfully with transformers==4.39.2
and datasets==2.18.0
.