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- Repository
- Ntizar/MasterMind
- Last source activity
- September 5, 2026 at 21:34
- Detected SKILL.md language
- Spanish
- Stars
- 2
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- 0
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Source instructions · Read-only preview- name
- timesfm-forecast
- description
- Usa a pronosticar series temporales con TimesFM 3.0.
- version
- 2.0.0
- tags
- ["timesfm","forecast","series-temporales","timesfm3","time-series","python"]
- related_skills
- ["timesfm-forecast","qlib-quant","monte-carlo-stock-simulator"]
# TimesFM — forecasting de series temporales (API 3.0)
> ⚠️ Corrección 2026-09-05 (auditoría): la v1 usaba `timesfm.TimesFm`/`model.forecast()` (TimesFM v1/v2). La versión actual **3.0** usa `from timesfm3 import TimesFM3Evaluator, ModelConfig` y `forecaster.predict_batch(...)`. Install real: `pip install timesfm[torch]`.
**Repo:** `https://github.com/google-research/timesfm` (Python, ~31K⭐).
## When to Use
- Cuando pidas **pronosticar una serie temporal** (modelo fundacional de Google) para tus datos.
## Uso (API 3.0)
```bash
pip install "timesfm[torch]"
```
```python
from timesfm3 import TimesFM3Evaluator, ModelConfig
model = TimesFM3Evaluator(config=ModelConfig(...))
forecasts = model.predict_batch(inputs, horizon=..., return_quantiles=True)
```
## Pitfalls
- **Install** `pip install "timesfm[torch]"`, no `pip install timesfm`.
- API **3.0**: `TimesFM3Evaluator`/`predict_batch`; no `TimesFm/forecast/forecast_with_quantiles` (v1/v2).
## Verificación
- `predict_batch(inputs, horizon=N)` y comprobar el forecast + quantiles.
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