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kage08 merged 2 commits into from
Feb 18, 2025
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Updated README #18

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Update README
kage08 Feb 18, 2025
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Merge branch 'AdityaLab:main' into main
kage08 Feb 18, 2025
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47 changes: 28 additions & 19 deletions README.md
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Original file line number Diff line number Diff line change
Expand Up @@ -8,7 +8,6 @@ Current repository contains the following models:
2. [MOMENT](https://arxiv.org/abs/2402.03885)
3. [TimesFM](https://arxiv.org/html/2310.10688v2)
4. [Chronos](https://arxiv.org/abs/2403.07815)
5. [MOIRAI](https://arxiv.org/abs/2402.02592)

More models will be added soon...

Expand All @@ -20,6 +19,12 @@ You can add the package to your project by running the following command:
pip install git+https://github.com/AdityaLab/Samay.git
```

For linux users with CUDA installed, you can install the package with GPU support by running:

```bash
pip install https://github.com/SamayAI/Samay/releases/download/v0.1.0/samay-0.1.0-cp311-cp311-linux_x86_64.whl
```

**Note:** If the installation fails because rust is missing run:

For MacOS:
Expand Down Expand Up @@ -53,35 +58,41 @@ curl -LsSf https://astral.sh/uv/install.sh | sh
uv sync --reinstall
```

## Usage Example
## Usage Examples

Check out example notebooks at `examples/` for more detailed examples. We also have google colab notebooks at `examples/colab/`.

### LPTM

#### Loading Model

```python
from samay.model import LPTMModel
from samay.dataset import LPTMDataset

repo = "lptm"
config = {
"context_len": 512,
"horizon_len": 192,
"backend": "gpu",
"per_core_batch_size": 32,
"domain": "electricity",
"task_name": "forecasting",
"forecast_horizon": 192,
"freeze_encoder": True, # Freeze the patch embedding layer
"freeze_embedder": True, # Freeze the transformer encoder
"freeze_head": False, # The linear forecasting head must be trained
}

lptm = LPTMModel(config=config, repo=repo)
model = LPTMModel(config)
```

#### Loading Dataset

```python
train_dataset = LPTMDataset(name="electricity", datetime_col='date', path='data/ETTh1.csv',
mode='train', context_len=config["context_len"], horizon_len=128)
val_dataset = LPTMDataset(name="electricity", datetime_col='date', path='data/ETTh1.csv',
mode='test', context_len=config["context_len"], horizon_len=config["horizon_len"])
from samay.dataset import LPTMDataset

train_dataset = LPTMDataset(
name="ett",
datetime_col="date",
path="./data/data/ETTh1.csv",
mode="train",
horizon=192,
)

finetuned_model = model.finetune(train_dataset)
```

#### Zero-Forecasting
Expand All @@ -92,8 +103,6 @@ avg_loss, trues, preds, histories = lptm.evaluate(val_dataset)

### TimesFM

Install the package: `pip install git+https://github.com/AdityaLab/Samay.git`.

#### Loading Model

```python
Expand Down Expand Up @@ -133,7 +142,7 @@ avg_loss, trues, preds, histories = tfm.evaluate(val_dataset)

### Support

Tested on Python 3.12, 3.13 on Linux (CPU + GPU) and MacOS (CPU). Supports NVIDIA GPUs.
Tested on Python 3.11-3.13 on Linux (CPU + GPU) and MacOS (CPU). Supports NVIDIA GPUs.
Support for Windows and Apple Silicon GPUs is planned.

## Citation
Expand All @@ -153,4 +162,4 @@ url={https://openreview.net/forum?id=vMMzjCr5Zj}

## Contact

If you have any feedback or questions, you can contact us via email: <hkamarthi3@gatech.edu>.
If you have any feedback or questions, you can contact us via email: <hkamarthi3@gatech.edu>, <badityap@cc.gatech.edu>.