EmbeddingGemma 2: an open, lightweight multimodal embedding model
deepmind.google·6d ago
AI Engineering
Hugging Face Blog·Sep 9·5 min read
IBM releases SOTA Granite Time Series PatchTST-FM-r2 model with commercial-friendly license
TL;DR
IBM has launched the Granite Time Series PatchTST-FM-r2 model, a state-of-the-art time-series forecasting tool that excels in zero-shot performance and is available under a commercial-friendly license.
✦ Why It Matters
Start using the Granite Time Series PatchTST-FM-r2 model today to improve your forecasting capabilities without extensive training.
Key Takeaways
- Utilize PatchTST-FM-r2 for immediate time-series forecasting.
- Leverage the model's dual licensing for commercial applications.
- Explore the model's architecture for insights into time-series relationships.
- Integrate with streaming applications using Confluent Cloud.
How It Works
PatchTST-FM-r2 employs conformer blocks that integrate multi-head self-attention with temporal convolution, allowing it to effectively model both long-range dependencies and local temporal structures in time-series data. This architecture enhances its ability to generate accurate forecasts by smoothing inter-patch predictions and capturing complex temporal relationships.