Knowledge Graph
Silytics Knowledge Graph
See how models, datasets, papers and organizations connect. Every link comes from public metadata: papers named on a model card, datasets and base models named in its tags, and the organization that published it. Click any dot to re-center; the smaller outer ring is two steps away.
Where Post-Training Quantization Breaks Text Embedders: A Measured Map Across Four Embedder Families
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Connections
- ThakiCloud/SKILLRET-Edge-22M-int4 Modelcited by
- ThakiCloud/SKILLRET-Embedding-0.6B Modelcited by
- ThakiCloud/SKILLRET-Edge-22M Modelcited by
- ThakiCloud/SKILLRET-Edge-22M-drift-mixed Modelcited by
- ThakiCloud/SKILLRET-Edge-109M Modelcited by
- Snowflake/snowflake-arctic-embed-xs Modeltwo steps away
- Snowflake/snowflake-arctic-embed-m Modeltwo steps away
- Quantize by Drift: Label-Free Mixed-Precision Post-Training Quantization for Text Embedders Papertwo steps away
- ThakiCloud/SKILLRET Datasettwo steps away
- Qwen/Qwen3-Embedding-0.6B Modeltwo steps away
- SkillRet: A Large-Scale Benchmark for Skill Retrieval in LLM Agents Papertwo steps away
Relationships are extracted automatically from public metadata and may be incomplete or wrong. Absence of a link does not mean absence of a relationship. Intelligence · Compare models