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Rolling out markdownlint-cli to lint Markdown (#15)
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.pre-commit-config.yaml

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rev: 1.19.1
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hooks:
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- id: blacken-docs
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- repo: https://github.com/igorshubovych/markdownlint-cli
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rev: v0.45.0
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hooks:
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- id: markdownlint
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args: [--config=pyproject.toml, --configPointer=/tool/markdownlint]
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- repo: https://github.com/jsh9/markdown-toc-creator
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rev: 0.0.10
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hooks:

README.md

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# ether0 Reward Model
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[![GitHub](https://img.shields.io/badge/github-%23121011.svg?style=for-the-badge&logo=github&logoColor=white)](https://github.com/Future-House/ether0)
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[![arXiv](https://img.shields.io/badge/arXiv-2506.17238-b31b1b.svg)](https://arxiv.org/abs/2506.17238)
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[![Project Status: Active](https://www.repostatus.org/badges/latest/active.svg)](https://www.repostatus.org/#active)
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![License](https://img.shields.io/badge/License-Apache_2.0-blue.svg)
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[![Tests](https://github.com/Future-House/ether0/actions/workflows/lint-test.yaml/badge.svg)](https://github.com/Future-House/ether0/actions)
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<a href="https://github.com/psf/black"><img alt="Code style: black" src="https://img.shields.io/badge/code%20style-black-000000.svg"></a>
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[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)
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[![python](https://img.shields.io/badge/python-3.11+-blue?style=flat&logo=python&logoColor=white)](https://www.python.org)
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[![Model on HF](https://huggingface.co/datasets/huggingface/badges/resolve/main/model-on-hf-md-dark.svg)](https://huggingface.co/futurehouse/ether0)
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[![Dataset on HF](https://huggingface.co/datasets/huggingface/badges/resolve/main/dataset-on-hf-md-dark.svg)](https://huggingface.co/datasets/futurehouse/ether0-benchmark)
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_ether0: a scientific reasoning model, dataset, and reward functions for chemistry._
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# ether0 Reward Model
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This repo contains the reward model for evaluating ether0 and similar models, along with utilities for working with the verifiable rewards in [our benchmark](https://huggingface.co/datasets/futurehouse/ether0-benchmark).
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This repo contains the reward model for evaluating ether0 and similar models,
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along with utilities for working with the verifiable rewards in
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[our benchmark](https://huggingface.co/datasets/futurehouse/ether0-benchmark).
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## Overview
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### Open Weights
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Please see our open-source weights on Hugging Face: https://huggingface.co/futurehouse/ether0
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Please see our open-source weights on Hugging Face:
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<https://huggingface.co/futurehouse/ether0>
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```python
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from transformers import AutoModelForCausalLM, AutoTokenizer
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### Open Test Set
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Please see our open-source benchmark (test set) on Hugging Face: https://huggingface.co/datasets/futurehouse/ether0-benchmark
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Please see our open-source benchmark (test set) on Hugging Face:
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<https://huggingface.co/datasets/futurehouse/ether0-benchmark>
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```python
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from datasets import load_dataset
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Next, start `ipython` with the relevant environment variables set:
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```bash
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ETHER0_REMOTES_API_BASE_URL="http://127.0.0.1:8000" ETHER0_REMOTES_API_TOKEN=abc123 ipython
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ETHER0_REMOTES_API_BASE_URL="http://127.0.0.1:8000" ETHER0_REMOTES_API_TOKEN=abc123 \
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ipython
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```
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And run the following Python code:

packages/remotes/README.md

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Or more manually:
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1. Go to this notebook: https://github.com/schwallergroup/ai4chem_course/blob/main/notebooks/07%20-%20Reaction%20Prediction/template_free.ipynb
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1. Go to [this notebook][1]
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2. Download the `USPTO480k_model_step_400000.pt`
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linked in the `trained_model_url` variable's linked Google Drive file:
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https://drive.google.com/uc?id=1ywJCJHunoPTB5wr6KdZ8aLv7tMFMBHNy
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<https://drive.google.com/uc?id=1ywJCJHunoPTB5wr6KdZ8aLv7tMFMBHNy>
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3. Set the environment variable `ETHER0_REMOTES_MOLTRANS_MODEL_PATH`
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to the downloaded PyTorch model's location,
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or place the model in the default checked `ether0` source code folder (`src/ether0`).
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[1]: https://github.com/schwallergroup/ai4chem_course/blob/main/notebooks/07%20-%20Reaction%20Prediction/template_free.ipynb
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## Serving
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To run the server:
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```bash
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ETHER0_REMOTES_API_TOKEN="abc123" \
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ETHER0_REMOTES_MOLTRANS_MODEL_PATH="/path/to/downloaded/USPTO480k_model_step_400000.pt" \
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ETHER0_REMOTES_MOLTRANS_MODEL_PATH="/path/to/USPTO480k_model_step_400000.pt" \
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ether0-serve
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```

pyproject.toml

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# This is designed to be invoked from within the test directory
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command_line = "-m pytest"
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[tool.markdownlint]
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no-inline-html = false
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[tool.markdownlint.line-length]
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code_block_line_length = 88 # Match ruff line-length
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line_length = 120 # Match ruff max-doc-length
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stern = true
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tables = false
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[tool.mypy]
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# Type-checks the interior of functions without type annotations.
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check_untyped_defs = true

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