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README.md
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license: apache-2.0
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language:
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pipeline_tag: question-answering
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# litert-community/Gecko-110m-en
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* Try out the gecko embedding model in the [google ai edge RAG SDK](https://ai.google.dev/edge/mediapipe/solutions/genai/rag). You can find the SDK on [GitHub](https://github.com/google-ai-edge/ai-edge-apis/tree/main/local_agents/rag) or follow our [android guide](https://ai.google.dev/edge/mediapipe/solutions/genai/rag/android)
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to install directly from Maven. We have also published a
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[sample app](https://github.com/google-ai-edge/ai-edge-apis/tree/main/examples/local_agents/rag).
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## Performance
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license: apache-2.0
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language:
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- en
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pipeline_tag: question-answering
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---
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# litert-community/Gecko-110m-en
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* Try out the gecko embedding model in the [google ai edge RAG SDK](https://ai.google.dev/edge/mediapipe/solutions/genai/rag). You can find the SDK on [GitHub](https://github.com/google-ai-edge/ai-edge-apis/tree/main/local_agents/rag) or follow our [android guide](https://ai.google.dev/edge/mediapipe/solutions/genai/rag/android)
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to install directly from Maven. We have also published a
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[sample app](https://github.com/google-ai-edge/ai-edge-apis/tree/main/examples/local_agents/rag).
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* Use the sentencepiece model as the tokenizer for the Gecko embedding model.
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## Performance
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