Python SDK
Complete reference for the 1.ML Python SDK.
oneml.Model
The core class for creating and managing ML models.
class Model:
def __init__(self, layers: List[Layer]):
def fit(self, data: Dataset, epochs: int):
def predict(self, input: Any) -> Any:
def deploy(self, name: str, env: str):
def save(self, path: str):
def load(cls, path: str) -> Model:oneml.Dataset
Manage and manipulate datasets for training.
class Dataset:
def load(cls, path: str) -> Dataset:
def split(self, ratio: float) -> Tuple[Dataset, Dataset]:
def transform(self, fn: Callable) -> Dataset:
def batch(self, size: int) -> Iterator:Example Usage
import oneml
# Initialize client
client = oneml.Client(api_key="your-key")
# Load and prepare data
data = oneml.Dataset.load("./data")
train, test = data.split(0.8)
# Create and train model
model = oneml.Model.from_preset("resnet50")
model.fit(train, epochs=10)
# Deploy
model.deploy("my-model")