Time Series Forecasting
MLX
Safetensors
apple-silicon
timestral
time-series
forecasting
quantile-regression
Instructions to use jbilcke/timestral-mlx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use jbilcke/timestral-mlx with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] hf download jbilcke/timestral-mlx --local-dir timestral-mlx
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
File size: 1,422 Bytes
d35e174 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 | """Build from an explicit clean temporary tree, excluding Apple filesystem metadata."""
import shutil
import subprocess
import sys
import tempfile
import zipfile
from pathlib import Path
ROOT=Path(__file__).resolve().parents[1]
with tempfile.TemporaryDirectory(prefix='timestral-build-') as tmp:
stage=Path(tmp)
for name in ('pyproject.toml','README.md','LICENSE','LICENSE-WEIGHTS','NOTICE','MANIFEST.in'):
shutil.copyfile(ROOT/name,stage/name)
(stage/'timestral_mlx').mkdir()
for path in (ROOT/'timestral_mlx').glob('*.py'):
if not path.name.startswith('._'):
shutil.copyfile(path,stage/'timestral_mlx'/path.name)
subprocess.run([sys.executable,'-m','build','--wheel','--no-isolation','--outdir',str(stage/'wheelhouse'),str(stage)],check=True)
(ROOT/'dist').mkdir(exist_ok=True)
for wheel in (stage/'wheelhouse').glob('*.whl'):
shutil.copyfile(wheel,ROOT/'dist'/wheel.name)
for path in (ROOT/'dist').glob('*.whl'):
if path.name.startswith('._'): continue
with zipfile.ZipFile(path) as z:
assert not any(any(p.startswith('._') or p in {'.DS_Store','__MACOSX'} for p in name.split('/')) for name in z.namelist())
assert any(name.endswith('/licenses/LICENSE-WEIGHTS') for name in z.namelist())
assert any(name.endswith('/licenses/NOTICE') for name in z.namelist())
print(f'Wheel inventory verified: {path.name}',flush=True)
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