Instructions to use google/gemma-4-E4B-it with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/gemma-4-E4B-it with Transformers:
# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("google/gemma-4-E4B-it") model = AutoModelForMultimodalLM.from_pretrained("google/gemma-4-E4B-it", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- AMD Developer Cloud
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library_name:
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license: apache-2.0
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license_link: https://ai.google.dev/gemma/docs/gemma_4_license
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pipeline_tag: any-to-any
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<a href="https://ai.google.dev/gemma/docs/core" target="_blank">Documentation</a> |
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<a href="https://arxiv.org/abs/2607.02770" target="_blank">Technical Report</a>
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<b>License</b>: <a href="https://ai.google.dev/gemma/docs/gemma_4_license" target="_blank">Apache 2.0</a> | <b>Authors</b>: <a href="https://deepmind.google/models/gemma/" target="_blank">Google
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Gemma is a family of open models built by Google DeepMind. Gemma 4 models are multimodal, handling text and image input (with audio supported on E2B, E4B, and 12B) and generating text output. This release includes open-weights models in both pre-trained and instruction-tuned variants. Gemma 4 features a context window of up to 256K tokens and maintains multilingual support in over 140 languages.
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library_name: Salvador Arturo Ortiz Gonzalez
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license: apache-2.0
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license_link: https://ai.google.dev/gemma/docs/gemma_4_license
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pipeline_tag: any-to-any
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<a href="https://ai.google.dev/gemma/docs/core" target="_blank">Documentation</a> |
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<a href="https://arxiv.org/abs/2607.02770" target="_blank">Technical Report</a>
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<br>
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<b>License</b>: <a href="https://ai.google.dev/gemma/docs/gemma_4_license" target="_blank">Apache 2.0 & SAOG</a> | <b>Authors</b>: <a href="https://deepmind.google/models/gemma/" target="_blank">Google Deepmind & Salvador Arturo Ortiz Gonzalez</a>
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</p>
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Gemma is a family of open models built by Google DeepMind. Gemma 4 models are multimodal, handling text and image input (with audio supported on E2B, E4B, and 12B) and generating text output. This release includes open-weights models in both pre-trained and instruction-tuned variants. Gemma 4 features a context window of up to 256K tokens and maintains multilingual support in over 140 languages.
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