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README.md
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---
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base_model:
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- gg-hf-gm/gemma-3-270m-it
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license: gemma
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tags:
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- gemma3
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- unsloth
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- gemma
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- google
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pipeline_tag: text-generation
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library_name: transformers
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extra_gated_heading: Access Gemma on Hugging Face
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extra_gated_prompt: >-
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To access Gemma on Hugging Face, you’re required to review and agree to
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Google’s usage license. To do this, please ensure you’re logged in to Hugging
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Face and click below. Requests are processed immediately.
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extra_gated_button_content: Acknowledge license
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---
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<div>
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<p style="margin-top: 0;margin-bottom: 0;">
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<em><a href="https://docs.unsloth.ai/basics/unsloth-dynamic-v2.0-gguf">Unsloth Dynamic 2.0</a> achieves superior accuracy & outperforms other leading quants.</em>
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</p>
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<div style="display: flex; gap: 5px; align-items: center; ">
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<a href="https://github.com/unslothai/unsloth/">
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<img src="https://github.com/unslothai/unsloth/raw/main/images/unsloth%20new%20logo.png" width="133">
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</a>
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<a href="https://discord.gg/unsloth">
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<img src="https://github.com/unslothai/unsloth/raw/main/images/Discord%20button.png" width="173">
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</a>
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<a href="https://docs.unsloth.ai/">
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<img src="https://raw.githubusercontent.com/unslothai/unsloth/refs/heads/main/images/documentation%20green%20button.png" width="143">
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</a>
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</div>
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</div>
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# Gemma 3 model card
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> [!Note]
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> This repository corresponds to the 270m **pre-trained** version of the Gemma 3 model using Quantization Aware Training (QAT).
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>
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> **The checkpoint in this repository is unquantized, please make sure to quantize with Q4_0 with your favorite tool**
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>
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> Thanks to QAT, the model is able to preserve similar quality as `bfloat16` while significantly reducing the memory requirements
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> to load the model.
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