Individual skill
marimo-batch
An opintionated skill to prepare a marimo notebook to make it ready for a scheduled run.
skills/marimo-batch/SKILL.md
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SKILL.mdcore · 4,696 bytesSKILL.mdcore · 4,696 bytesSKILL.mdcore · 4,696 bytesSKILL.mdcore · 4,696 bytesSKILL.mdcore · 4,696 bytesSKILL.mdcore · 4,696 bytesSKILL.mdcore · 4,696 bytesSKILL.mdcore · 4,696 bytesreferences/grid.pyruns · 6,080 bytesreferences/starting-point.pyruns · 6,224 bytes
Read excerpt
Pydantic is a great way to declare a source of truth for a batch job, especially for ML. You can declare something like:
```python
from pydantic import BaseModel, Field
class ModelParams(BaseModel):
sample_size: int = Field(
default=1024 * 4, description="Number of training samples per epoch."
)
learning_rate: float = Field(default=0.01, description="Learning rate for the optimizer.")
```
You can fill these model params with two methods too, you can imagine a form in the UI.