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Acumen

This codebase implements incentivized GRPO reinforcement learning for reasoning models on Bittensor.

1. Install uv

curl -LsSf https://astral.sh/uv/install.sh | sh

2. Create .venv

uv venv
source .venv/bin/activate

3. Install Dependencies

uv sync

4. Set your Chutes API key

- Visit [chutes.ai](https://chutes.ai)
- Create an account
- Generate an API key from your account settings
- Set your chute api env var:
CHUTES_API_KEY=your_chutes_api_key

5. Set your Cloudflare R2

  • Go to Cloudflare Dashboard
  • Navigate to R2
  • Create a new bucket
  • Generate API tokens with read/write permissions
  • Set your R2 env vars:
Cloudflare R2 Configuration
R2_ACCESS_KEY_ID=your_r2_access_key
R2_SECRET_ACCESS_KEY=your_r2_secret_key
R2_ENDPOINT_URL=your_r2_endpoint_url

6. Run your miner or validator

# Validator + Miner
python3 run.py 

# Only Validator
python3 run.py --no_miner

# Only Miner
python3 run.py --no_validator
# The MIT License (MIT)
# © 2025 Acumen

# Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated
# documentation files (the “Software”), to deal in the Software without restriction, including without limitation
# the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software,
# and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

# The above copyright notice and this permission notice shall be included in all copies or substantial portions of
# the Software.

# THE SOFTWARE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO
# THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL
# THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION
# OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER
# DEALINGS IN THE SOFTWARE.

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Incentivized GRPO Reinforcement Learning for reasoning models on Bittensor.

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  • Python 69.3%
  • Jupyter Notebook 30.7%