Alibaba-NLP/gte-reranker-modernbert-base

Alibaba-NLP released the gte-reranker-modernbert-base, a ModernBERT-based reranker model under the Apache-2.0 license, designed for RAG and search reranking workflows. The 1.1 GB model is available on Hugging Face and can run on CPU, Apple Silicon, or consumer GPUs, though its hosting status is external and scan is pending.

Alibaba-NLP/gte-reranker-modernbert-base Alibaba-NLP/gte-reranker-modernbert-base: Apache-2.0 ModernBERT-based GTE reranker for practical RAG and search reranking workflows. License: apache-2.0. external huggingface metadata. Scan: pending. - License - apache-2.0 - Size - 1.1 GB - Demand - 500 upstream downloads - Trust - Needs review 0/100 - Trusted download - External metadata; mirror requestable - Run fit - Easy local embedding fit: CPU, Apple Silicon, or a small consumer GPU is usually enough for smoke tests - Files - 0 hosted / 1 total - Scan status - pending - Hosting status - external - Upstream - Alibaba-NLP/gte-reranker-modernbert-base - Declared license - apache-2.0 - Pipeline - text-ranking - Library - Transformers - Task categories - text-ranking About this artifact Alibaba-NLP/gte-reranker-modernbert-base is included in Hugging Bay's compact resilience fallback for high-demand open AI artifacts. Live Postgres metadata, hosted files, hashes, and reviews take precedence whenever available. Trusted download External metadata; mirror requestable. Use upstream for now or add demand for a reviewed Hugging Bay mirror. - Hosted files - 0 of 1 - Reviewed peer-assisted fallbacks - 0 - Download plan Download-plan JSON /api/artifacts/hf-model-alibaba-nlp-gte-reranker-modernbert-base/download-plan - Trust bundle Trust-bundle JSON /api/trust-bundles/hf-model-alibaba-nlp-gte-reranker-modernbert-base - Review summary Review-summary JSON /api/artifacts/hf-model-alibaba-nlp-gte-reranker-modernbert-base/review-summary - Distribution Reviewed peer-fallback JSON /api/artifacts/hf-model-alibaba-nlp-gte-reranker-modernbert-base/distribution Can I run this? Easy local embedding fit. CPU, Apple Silicon, or a small consumer GPU is usually enough for smoke tests. Start with the local kit, verify hashes, then run a small inference or embedding check before production use. - Estimated footprint - 1.1 GB - Suggested runners - Transformers - Runtime files - 0 - Local kit Local run kit /local-kit/hf-model-alibaba-nlp-gte-reranker-modernbert-base Run-fit warnings: No runtime weight file is indexed yet.; Hugging Bay is showing metadata only until reviewed hosted files exist. - License: pass - apache-2.0 - Provenance: pass - Alibaba-NLP/gte-reranker-modernbert-base - Scan: warn - pending - Hosted files: warn - external metadata only - Signed manifest: fail - not final yet - Community: warn - no reviews yet - Benchmarks: warn - no benchmark evidence Machine-readable card Open interactive artifact page / /artifact/hf-model-alibaba-nlp-gte-reranker-modernbert-base