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README.md
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base_model:
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library_name: transformers
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license: gemma
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tags:
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- unsloth
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- gemma3
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- gemma
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- google
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---
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<div>
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<
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</p>
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<p style="margin-bottom: 0;">
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<em><a href="https://docs.unsloth.ai/basics/tutorial-how-to-run-gemma-3-effectively">Read our Guide</a> to see how to Run Gemma 3 correctly.</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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<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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<h1 style="margin-top: 0rem;">✨ Fine-tune Gemma 3 with Unsloth!</h1>
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</div>
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- Fine-tune Gemma 3 (270M) for free using our Google [Colab notebook here](https://docs.unsloth.ai/get-started/unsloth-notebooks)!
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- Read our Blog about Gemma 3 support: [unsloth.ai/blog/gemma3](https://unsloth.ai/blog/gemma3)
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- View the rest of our notebooks in our [docs here](https://docs.unsloth.ai/get-started/unsloth-notebooks).
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| Unsloth supports | Free Notebooks | Performance | Memory use |
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|-----------------|--------------------------------------------------------------------------------------------------------------------------|-------------|----------|
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| **Gemma 3 (4B)** | [▶️ Start on Colab](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Gemma3_(4B).ipynb) | 2x faster | 80% less |
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| **Gemma-3n-E4B** | [▶️ Start on Colab](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Gemma3N_(4B)-Conversational.ipynb) | 2x faster | 60% less |
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| **Gemma-3n-E4B (Audio)** | [▶️ Start on Colab](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Gemma3N_(4B)-Audio.ipynb) | 2x faster | 60% less |
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| **GRPO with Gemma 3 (1B)** | [▶️ Start on Colab](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Gemma3_(1B)-GRPO.ipynb) | 2x faster | 80% less |
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| **Gemma 3 (4B) Vision** | [▶️ Start on Colab](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Gemma3_(4B)-Vision.ipynb) | 2x faster | 60% less |
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# Gemma 3 model card
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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 and 270M sizes.
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[jax]: https://github.com/jax-ml/jax
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[ml-pathways]: https://blog.google/technology/ai/introducing-pathways-next-generation-ai-architecture/
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[sustainability]: https://sustainability.google/operating-sustainably/
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[gemini-2-paper]: https://arxiv.org/abs/2312.11805
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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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<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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- **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, for the 4B, 12B, and 27B sizes.
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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 and 270M sizes.
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[jax]: https://github.com/jax-ml/jax
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[ml-pathways]: https://blog.google/technology/ai/introducing-pathways-next-generation-ai-architecture/
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[sustainability]: https://sustainability.google/operating-sustainably/
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[gemini-2-paper]: https://arxiv.org/abs/2312.11805
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