MODEL PROFILE

minilm-tekla-attr-embed-v1

teknovizier · minilm-tekla-attr-embed-v1

This is a sentence-transformers model finetuned from sentence-transformers/all-MiniLM-L12-v2 for matching Tekla Structures attributes with natural language queries. It enables semantic search and attribute matching by mapping natural language descriptions to Tekla attribute names. This model is specifically designed for **Tekla Structures attribute matching**. It converts natural language queries (e.g., "bolt name from catalog") into embeddings that can be matched against Tekla attribute names (e.g., "BOLT_FULL_NAME"). For optimal performance, text should be normalized before encoding: 1. **Convert to lowercase** 2. **Replace underscores and hyphens with spaces** 3. **Remove non-alphanumeric characters**

Context windowNot disclosed
Input → OutputText → Embedding
Model weightsNot verified
Profile updated2026/11/2 19:15:49
OVERVIEW

Model overview

This is a sentence-transformers model finetuned from sentence-transformers/all-MiniLM-L12-v2 for matching Tekla Structures attributes with natural language queries. It enables semantic search and attribute matching by mapping natural language descriptions to Tekla attribute names. This model is specifically designed for **Tekla Structures attribute matching**. It converts natural language queries (e.g., "bolt name from catalog") into embeddings that can be matched against Tekla attribute names (e.g., "BOLT_FULL_NAME"). For optimal performance, text should be normalized before encoding: 1. **Convert to lowercase** 2. **Replace underscores and hyphens with spaces** 3. **Remove non-alphanumeric characters**

Key features

特点摘要待依据来源补齐,不凭模型名称推断能力。

Limitations & considerations

Sources are insufficient to establish specific limitations. Verify task performance, latency, data policies, licensing and version lifecycle.

PRICING & COST

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INDEPENDENT BENCHMARKS

Public benchmarks & run configuration

暂无已采集的可核验公开评分。模型未上榜不代表能力较低。

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Frequently asked questions

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Sources & traceability

许可证:gpl-3.0。模型介绍与第三方评测均以原来源的具体版本和方法为准。