forecasting-reversolisted

# Reverso Time Series Forecasting Produce zero-shot univariate time series forecasts using the Reverso foundation model family (arXiv:2602.17634), implemented in NumPy/Numba for CPU-only container execution. ## Setup (run once per conversation) ```bash uv pip install numba --system --break-system-packages cp /mnt/skills/user/forecasting-reverso/scripts/reverso.py /home/claude/reverso.py cp /mnt/skills/user/forecasting-reverso/scripts/load_checkpoint.py /home/claude/load_checkpoint.py ``` ## Obtaining Weights Two paths depending on network access: ### Path A: Direct download (HuggingFace allow-listed) ```python import urllib.request, os os.makedirs("/tmp/reverso", exist_ok=True) url = "https://huggingface.co/shinfxh/reverso/resolve/main/checkpoints/reverso_small/checkpoint.pth" urllib.request.urlretrieve(url, "/tmp/reverso/checkpoint.pth") ``` ### Path B: User upload (HuggingFace not accessible) If the download fails with a network error, tell the user: > I can't reach HuggingFace from this environment. Please download the checkpoint from > https://huggingface.co/shinfxh/reverso/blob/main/checkpoints/reverso_small/checkpoint.pth > and upload it here. Then load from `/mnt/user-data/uploads/checkpoint.pth`. ### Loading weights ```python from load_checkpoint import load_checkpoint weights = load_checkpoint("/tmp/reverso/checkpoint.pth") # or upload path ``` ## Model Configuration Reverso Small uses this config (matching the published `args.json`): ```python from rev