Embeddingtransformerspytorchsafetensorsbertfeature-extractionarxiv:2310.07554arxiv:2309.07597license:mittext-embeddings-inferenceendpoints_compatibledeploy:azureregion:us
컨텍스트
512 토큰
최대 출력
256 토큰
출시일
2023. 10. 9.
제공자
1
Overview
llm-embedder is a large language model developed by BAAI. It supports 512 tokens context and is available through 1 API provider(s).
Key Highlights
- Embedding
Brand
BAAI
Organization
국가: China
View all models, pricing and details from BAAI.
Specifications
Basic Information
| 모델 | llm-embedder |
| 브랜드 | BAAI |
| Version | Unknown / Not disclosed |
| Model Type | transformers |
| 상태 | stable |
| 출시일 | 2023. 10. 9. |
| 인기 | 53411 |
Architecture
| Parameter Size | 109.5M |
| 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 | Unknown / Not disclosed |
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 | mit |
| Commercial Use | Unknown / Not disclosed |
| Open Source | Yes |
Provider & Pricing
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 llm-embedder?
llm-embedder is a large language model developed by BAAI.
Who developed llm-embedder?
llm-embedder was developed by BAAI. You can learn more on the brand page or official website.
What is the context length of llm-embedder?
llm-embedder supports up to 512 tokens of context.
How much does llm-embedder API cost?
API pricing for llm-embedder starts at ₩0/1M per 1M input tokens and ₩0/1M per 1M output tokens. See the pricing table above for provider-specific rates.