Question Answering
LiteRT
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- ---
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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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- ---
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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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+ ---
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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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