pfnet/plamo-embedding-1b
sentence-similarity model by pfnet
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Model card & documentation
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日本語版のREADME/Japanese README PLaMo-Embedding-1B is a Japanese text embedding model developed by Preferred Networks, Inc. It can convert Japanese text input into numerical vectors and can be used for a wide range of applications, including information retrieval, text classification, and clustering. As of early April 2025, it achieved top-class scores on JMTEB, a benchmark for Japanese text embedding. It demonstrated particularly outstanding performance, especially in retrieval tasks. PLaMo-Embedding-1B is released under the Apache v2.0 license, and you can use it freely, including for commercial purposes. For technical details, please refer to the following Tech Blog post (Ja): https://tech.preferred.jp/ja/blog/plamo-embedding-1b/ Note: For encodedocument and encodequery, texts exceeding the model's maximum context length of 4096 will be truncated. Be especially aware that for encodequery, a prefix is added internally, making the effective maximum context length slightly shorter. We conducted a performance evaluation using…
Read the full model card ↗ · Preview checked 2026-10-02T06:41:31.926Z
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- PLaMo-Embedding-1B
- Model Overview
- Usage
- Requirements
- Sample Code
- Benchmarks
- Model Details
- License
- How to cite
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Model overview
pfnet/plamo-embedding-1b is a sentence-similarity model repository published by pfnet on Hugging Face. The source reports the transformers library.
This page summarizes Hub metadata. For intended use, training data, evaluation results and limitations, consult the original model card.
Model facts
- Task
- sentence-similarity
- Library
- transformers
- Recent downloads (30 days)
- 128,900
- Cumulative likes
- 48
- Hugging Face trending score
- 0
- Reported safetensors parameters
- 1,050,644,480
- Architecture
- PlamoBiModel
- License
- apache-2.0
- Access
- Not gated by Hugging Face
- Created
- 2025-04-11T08:43:31.000Z
- Last modified
- 2025-08-28T10:22:44.000Z
Compatibility and lineage
Reported languages: ja
Base-model lineage was not included.
Parameter count is not a RAM/VRAM requirement. Check precision, quantization, context length and runtime compatibility in the model card; no hardware or API-cost claim is inferred here.
Use and evaluate
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Source and freshness
Source: Hugging Face Hub. Metadata observed 2026-10-02T06:40:29.845Z. Daily imports are snapshots, not real-time monitoring.
Popularity and source listings do not establish security, suitability, licensing rights or benchmark performance.
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