{"slug": "answerdotai-modernbert-base", "title": "answerdotai/ModernBERT-base", "summary": "Answerdotai released ModernBERT-base, a 1.2 GB encoder model under Apache-2.0 license, designed for fill-mask tasks with easy local fit on consumer hardware. The model is available via Hugging Bay with external metadata and pending security scan, requiring user verification before production use.", "body_md": "# answerdotai/ModernBERT-base\n\nanswerdotai/ModernBERT-base: ModernBERT-base encoder model with Apache-2.0 licensing and strong practical NLP utility. License: apache-2.0. external huggingface metadata. Scan: pending.\n\n- License\n- apache-2.0\n- Size\n- 1.2 GB\n- Demand\n- 500 upstream downloads\n- Trust\n- Needs review 0/100\n- Trusted download\n- External metadata; mirror requestable\n- Run fit\n- Easy local fit: CPU, Apple Silicon, or a small consumer GPU is usually enough for smoke tests\n- Files\n- 0 hosted / 1 total\n- Scan status\n- pending\n- Hosting status\n- external\n- Upstream\n- answerdotai/ModernBERT-base\n- Declared license\n- apache-2.0\n- Pipeline\n- fill-mask\n- Library\n- Transformers\n- Task categories\n- fill-mask\n\n## About this artifact\n\nanswerdotai/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.\n\n## Trusted download\n\nExternal metadata; mirror requestable. Use upstream for now or add demand for a reviewed Hugging Bay mirror.\n\n- Hosted files\n- 0 of 1\n- Reviewed peer-assisted fallbacks\n- 0\n- Download plan\n[Download-plan JSON](/api/artifacts/hf-model-answerdotai-modernbert-base/download-plan)- Trust bundle\n[Trust-bundle JSON](/api/trust-bundles/hf-model-answerdotai-modernbert-base)- Review summary\n[Review-summary JSON](/api/artifacts/hf-model-answerdotai-modernbert-base/review-summary)- Distribution\n[Reviewed peer-fallback JSON](/api/artifacts/hf-model-answerdotai-modernbert-base/distribution)\n\n## Can I run this?\n\nEasy local 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.\n\n- Estimated footprint\n- 1.2 GB\n- Suggested runners\n- Transformers, vLLM\n- Runtime files\n- 0\n- Local kit\n[Local run kit](/local-kit/hf-model-answerdotai-modernbert-base)\n\nRun-fit warnings: No runtime weight file is indexed yet.; Hugging Bay is showing metadata only until reviewed hosted files exist.\n\n- License: pass - apache-2.0\n- Provenance: pass - answerdotai/ModernBERT-base\n- Scan: warn - pending\n- Hosted files: warn - external metadata only\n- Signed manifest: fail - not final yet\n- Community: warn - no reviews yet\n- Benchmarks: warn - no benchmark evidence\n\n## Machine-readable card\n\n[Open interactive artifact page](/#/artifact/hf-model-answerdotai-modernbert-base)", "url": "https://wpnews.pro/news/answerdotai-modernbert-base", "canonical_source": "https://huggingbay.xyz/artifact/hf-model-answerdotai-modernbert-base", "published_at": "2026-07-07 00:00:00+00:00", "updated_at": "2026-07-11 04:42:53.560427+00:00", "lang": "en", "topics": ["artificial-intelligence", "large-language-models", "ai-products", "ai-tools", "developer-tools"], "entities": ["answerdotai", "ModernBERT-base", "Hugging Bay", "Transformers", "vLLM"], "alternates": {"html": "https://wpnews.pro/news/answerdotai-modernbert-base", "markdown": "https://wpnews.pro/news/answerdotai-modernbert-base.md", "text": "https://wpnews.pro/news/answerdotai-modernbert-base.txt", "jsonld": "https://wpnews.pro/news/answerdotai-modernbert-base.jsonld"}}