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README.md
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# Uploaded finetuned model
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- **Developed by:** atharvataras
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---
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# Gemma 3 model card
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**Model Page**: [Gemma](https://ai.google.dev/gemma/docs/core)
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**Resources and Technical Documentation**:
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* [Gemma 3 Technical Report][g3-tech-report]
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* [Responsible Generative AI Toolkit][rai-toolkit]
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* [Gemma on Kaggle][kaggle-gemma]
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* [Gemma on Vertex Model Garden][vertex-mg-gemma3]
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**Terms of Use**: [Terms][terms]
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**Authors**: Google DeepMind
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## Model Information
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Summary description and brief definition of inputs and outputs.
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### Description
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Gemma is a family of lightweight, state-of-the-art open models from Google,
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built from the same research and technology used to create the Gemini models.
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Gemma 3 models are multimodal, handling text and image input and generating text
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output, with open weights for both pre-trained variants and instruction-tuned
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variants. Gemma 3 has a large, 128K context window, multilingual support in over
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140 languages, and is available in more sizes than previous versions. Gemma 3
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models are well-suited for a variety of text generation and image understanding
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tasks, including question answering, summarization, and reasoning. Their
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relatively small size makes it possible to deploy them in environments with
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limited resources such as laptops, desktops or your own cloud infrastructure,
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democratizing access to state of the art AI models and helping foster innovation
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for everyone.
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### Inputs and outputs
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- **Input:**
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- Text string, such as a question, a prompt, or a document to be summarized
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- Images, normalized to 896 x 896 resolution and encoded to 256 tokens
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each
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- Total input context of 128K tokens for the 4B, 12B, and 27B sizes, and
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32K tokens for the 1B size
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- **Output:**
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- Generated text in response to the input, such as an answer to a
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question, analysis of image content, or a summary of a document
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- Total output context of 8192 tokens
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# Uploaded finetuned model
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- **Developed by:** atharvataras
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