Embeddingsentence-transformerspytorchtfrustonnxsafetensorsopenvinobertfeature-extractionsentence-similaritytransformersendataset:s2orcdataset:flax-sentence-embeddings/stackexchange_xmldataset:ms_marcodataset:gooaqdataset:yahoo_answers_topicsdataset:code_search_netdataset:search_qadataset:eli5dataset:snlidataset:multi_nlidataset:wikihowdataset:natural_questionsdataset:trivia_qadataset:embedding-data/sentence-compressiondataset:embedding-data/flickr30k-captionsdataset:embedding-data/altlexdataset:embedding-data/simple-wikidataset:embedding-data/QQPdataset:embedding-data/SPECTERdataset:embedding-data/PAQ_pairsdataset:embedding-data/WikiAnswersarxiv:1904.06472arxiv:2102.07033arxiv:2104.08727arxiv:1704.05179arxiv:1810.09305base_model:nreimers/MiniLM-L6-H384-uncasedbase_model:quantized:nreimers/MiniLM-L6-H384-uncasedlicense:apache-2.0eval-resultstext-embeddings-inferenceendpoints_compatibledeploy:sagemakerdeploy:azureregion:us
컨텍스트
512 토큰
최대 출력
256 토큰
출시일
2022. 3. 2.
제공자
1
Overview
all-MiniLM-L6-v2 is a large language model developed by UKP Lab. It supports 512 tokens context and is available through 1 API provider(s).
Key Highlights
- Embedding
Brand
UKP Lab
Organization
국가: Germany
View all models, pricing and details from UKP Lab.
Specifications
Basic Information
| 모델 | all-MiniLM-L6-v2 |
| 브랜드 | UKP Lab |
| Version | 6 |
| Model Type | sentence-transformers |
| 상태 | stable |
| 출시일 | 2022. 3. 2. |
| 인기 | 252279890 |
Architecture
| Parameter Size | 22.7M |
| Architecture Type | bert |
| Attention Mechanism | Unknown / Not disclosed |
| Tokenizer | Unknown / Not disclosed |
| Vocabulary Size | Unknown / Not disclosed |
Context & I/O
| 컨텍스트 | 512 tokens |
| 최대 출력 | 256 tokens |
| Modalities | Embedding |
| Languages | en |
Capabilities
| Vision | No |
| Audio | No |
| Reasoning | No |
| Function Call | No |
| MCP | No |
| JSON Mode | No |
| Embedding | Yes |
Training Data
| Training Dataset | Unknown / Not disclosed |
| Estimated Data Size | Unknown / Not disclosed |
| Knowledge Cutoff | Unknown / Not disclosed |
Inference & Deployment
| API Access | Yes |
| VRAM Estimate | Unknown / Not disclosed |
| Quantization Support | Unknown / Not disclosed |
| Hardware Requirements | Unknown / Not disclosed |
Safety & Compliance
| Safety Evaluations | Unknown / Not disclosed |
| Content Policy | Unknown / Not disclosed |
| Region Restrictions | Unknown / Not disclosed |
License & Pricing
| License | apache-2.0 |
| Commercial Use | Unknown / Not disclosed |
| Open Source | Yes |
Provider & Pricing
| 제공자 | 입력 | 출력 | 캐시 | 배치 | 웹사이트 |
|---|---|---|---|---|---|
| sentence-transformers | ₩0/1M | ₩0/1M | - | - | 웹사이트 방문 |
가격 변동
가격 변동 기록이 없습니다.
벤치마크
No benchmark data available.
Changelog
- Page created / data imported2026. 9. 23.
- Last updated2026. 9. 23.
FAQ
What is all-MiniLM-L6-v2?
all-MiniLM-L6-v2 is a large language model developed by UKP Lab.
Who developed all-MiniLM-L6-v2?
all-MiniLM-L6-v2 was developed by UKP Lab. You can learn more on the brand page or official website.
What is the context length of all-MiniLM-L6-v2?
all-MiniLM-L6-v2 supports up to 512 tokens of context.
How much does all-MiniLM-L6-v2 API cost?
API pricing for all-MiniLM-L6-v2 starts at ₩0/1M per 1M input tokens and ₩0/1M per 1M output tokens. See the pricing table above for provider-specific rates.