liangjianshu/multimodal-image-retrieval
多模态检索实战：意图识别、Prompt 工程、Qwen LoRA、EmbeddingGemma 2 与 InfoNCE 对比学习。含真实演示、自有数据接入、训练评测及 RAG 检索组件学习指南。
Rising: created 4d ago
- 101stars
- 0forks
- 0open issues
- updated 1d ago
About multimodal-image-retrieval
multimodal-image-retrieval is a free, open-source RAG and AI search tool by liangjianshu, written mainly in Python. 多模态检索实战：意图识别、Prompt 工程、Qwen LoRA、EmbeddingGemma 2 与 InfoNCE 对比学习。含真实演示、自有数据接入、训练评测及 RAG 检索组件学习指南。. It has 101 GitHub stars and 0 forks, and was last updated 1d ago. It's released under the MIT license, a standard open-source license.
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multimodal-image-retrieval FAQ
Can I use multimodal-image-retrieval commercially?
Yes. MIT is a permissive license: commercial use is allowed as long as you keep the license notice. This is a plain-English summary, not legal advice.
Is multimodal-image-retrieval free?
Yes. multimodal-image-retrieval is open source and free to use. It's released under the MIT license, a standard open-source license.
Does multimodal-image-retrieval run on a Mac?
The project doesn't say. Check its installation guide before you start.
Does multimodal-image-retrieval need a GPU?
The project doesn't state hardware needs. AI models generally run much faster with a GPU.
Is multimodal-image-retrieval still maintained?
Yes. It was last updated 1d ago and has 0 open issues on GitHub.
What are alternatives to multimodal-image-retrieval?
Similar free, open-source tools include qdrant, ragflow, weaviate, storm.
Related topics
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