1.24.0

1.24.0

New Features

• Feature Store: Added tile-based aggregation support with a new Feature API for efficient and
  point-in-time correct time-series feature computation using pre-computed tiles stored in Dynamic Tables.

• Registry: Added auto-signature inference for SentenceTransformer models. When logging a SentenceTransformer
  model, sample_input_data is now optional. If not provided, the signature is automatically inferred from
  the model's embedding dimension. Supported methods: encode, encode_query, encode_document,
  encode_queries, encode_documents.

import sentence_transformers
from snowflake.ml.registry import Registry

# Create model
model = sentence_transformers.SentenceTransformer("all-MiniLM-L6-v2")

# Log model without sample_input_data - signature is auto-inferred
registry = Registry(session)
mv = registry.log_model(
    model=model,
    model_name="my_sentence_transformer",
    version_name="v1",
)

# Run inference with auto-inferred signature (input: "text", output: "output")
import pandas as pd
result = mv.run(pd.DataFrame({"text": ["Hello world"]}))

Bug Fixes

Behavior Changes

Deprecations