tidepool/tide-embed-large
Embeddings330M paramssafetensorsLicense: miten#retrieval#sentence-embeddings
Updated Sep 4, 2026
Part of the Open Pace seed catalog. Weights are listed for the preview and become downloadable at launch.
Overview
The 1,024-dimension sibling of tide-embed-small for higher-recall search.
tidepool/tide-embed-large is a 330M-parameter embeddings model, published in safetensors under the mit license.
Intended use
- Embeddings in en.
- Research, prototypes and products that keep a person in the loop.
- Fine-tuning as a starting point for a narrower task.
How to use
# Command-line client (planned; the shape may change)
pace pull tidepool/tide-embed-large
# Python (planned)
from openpace import load
model = load("tidepool/tide-embed-large")Limitations
- It can state wrong things fluently. Check facts that matter.
- Quality drops on languages and domains that were thin in its training data.
- It reflects biases present in public text.
License
Released under mit. Read the license file before using the weights commercially.