Model Detail
granite-embedding-97m-multilingual-r2
—granite-embedding-97m-multilingual-r2 is a large language model with 49M parameters released by ibm-granite. The model is registered under the feature-extraction pipeline tag on Hugging Face, distributed under the permissive apache-2.0 license.
granite-embedding-97m-multilingual-r2 ships with 49M parameters. The apache-2.0 license is permissive, allowing commercial deployment and derivative work without per-seat fees, though attribution requirements still apply.
Downloads of granite-embedding-97m-multilingual-r2 have moved +2217.7% over the trailing thirty days. That is a slight downtrend, consistent with normal cooling as newer models compete for the same workloads. These numbers are signal, not guarantee — week-over-week download counts on Hugging Face also reflect mirror traffic, CI scrapes, and one-off benchmarking runs.
granite-embedding-97m-multilingual-r2 is best fit for general-purpose chat and instruction-following workloads, and semantic search, retrieval, and clustering pipelines. Treat this as a starting matrix rather than a benchmark verdict — the right deployment usually depends on the specific evaluation suite that mirrors your workload.
GRANITE : a Byzantine-Resilient Dynamic Gossip Learning Framework
arXiv:2504.17471v2 Announce Type: replace-cross Abstract: Gossip Learning (GL) is a decentralized learning paradigm where users iteratively exchange and aggregate models with a small set of neighboring peers. Recent approaches rely on dynamic communication graphs built using Random Peer Sampling (RP
