metadata
datasets:
- Alexhf825/dataset-AutoMR-pangu
language:
- en
metrics:
- accuracy
base_model:
- FreedomIntelligence/openPangu-Embedded-7B
AutoMR for Pangu
This project equips the Pangu model with the AutoMR reasoning framework, optimized for Huawei Ascend hardware.
🌳 Project Structure
.
├── AMC.SH
├── automr
│ ├── config.py
│ ├── dag.py
│ ├── data_loader.py
│ ├── evaluator.py
│ ├── __init__.py
│ ├── model.py
│ ├── strategies.py
│ ├── trainer.py
│ └── utils.py
├── checkpoints
│ └── MATH
├── embedder_server.sh
├── generator_server.sh
├── main.py
├── math_train.sh
└── processed_data
├── AMC
└── MATH
🔧 1. Installation
a. Clone the Project Repository
hf download Alexhf825/AutoMR-pangu --local-dir AutoMR-pangu
cd AutoMR-pangu
b. Install Dependencies
c. Download Datasets
This command will download the datasets and place them in the ./processed_data directory, matching the project structure.
hf download Alexhf825/dataset-AutoMR-pangu --repo-type=dataset --local-dir=./
🚀 2. Start the Servers
This project requires two services running in an OpenAI-API style. Please run the following commands in two separate terminal sessions.
Start the Embedder Server:
bash embedder_server.sh
Start the Generator Server:
bash generator_server.sh
📈 3. Run Evaluation
A pre-trained checkpoint (MATH) is provided. You can directly evaluate the model on the AMC dataset using the following command:
bash AMC.sh
🏋️ 4. Run Training
You can also train the model from scratch on the MATH dataset by running:
bash math_train.sh