Tencent/WeMM-Embedding
WeMM-Embedding is a family of universal multimodal embedding models by the WeChat Vision Team at Tencent, supporting multimodal understanding and retrieval.
- Stars
- 1.8k
- Forks
- 123
- Open issues
- 1
- Last push
- 1mo ago
About WeMM-Embedding
WeMM-Embedding is a free, open-source RAG and AI search tool by Tencent, written mainly in Python. WeMM-Embedding is a family of universal multimodal embedding models by the WeChat Vision Team at Tencent, supporting multimodal understanding and retrieval. It has 1.8k GitHub stars and 123 forks, and was last updated 1mo ago. GitHub doesn't detect a standard license, so check the repository before using it commercially.
- License
- Not detected
- Language
- Python
- Stars
- 1,777
- Last update
- 1mo ago
- Runs on Mac
- Not stated
- GPU
- Not stated
- Paid API key
- Not required
- Self-hostable
- Yes
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WeMM-Embedding FAQ
Is WeMM-Embedding free?
Yes. WeMM-Embedding is open source and free to use. GitHub doesn't detect a standard license, so check the repository before using it commercially.
Does WeMM-Embedding run on a Mac?
The project doesn't say. Check its installation guide before you start.
Does WeMM-Embedding need a GPU?
The project doesn't state hardware needs. AI models generally run much faster with a GPU.
Is WeMM-Embedding still maintained?
It was last updated 1mo ago. Check recent issues on GitHub to judge how active it is.
What are alternatives to WeMM-Embedding?
Similar free, open-source tools include FlagEmbedding, txtai, LightRAG, storm.