gemma-3-1b-it

Gemma 3 model card Model Page: Gemma Resources and Technical Documentation: Gemma 3 Technical Report Responsible Generative AI Toolkit Gemma on Kaggle Gemma on Vertex Model Garden Terms of Use: Terms Authors: Google DeepMind Model Information Summary description and brief definition of inputs and outputs. Description Gemma is a family of lightweight, state-of-the-art open models from Google, built from the same research and technology used to create the Gemini models. Gemma 3 models are multimodal, handling text and image input and generating text output, with open weights for both pre-trained variants and instruction-tuned variants. Gemma 3 has a large, 128K context window, multilingual support in over 140 languages, and is available in more sizes than previous versions. Gemma 3 models are well-suited for a variety of text generation and image understanding tasks, including question answering, summarization, and reasoning. Their relatively small size makes it possible to deploy them in environments with limited resources such as laptops, desktops or your own cloud infrastructure, democratizing access to state of the art AI models and helping foster innovation for everyone. Inputs and outputs Input: Text string, such as a question, a prompt, or a document to be summarized Images, normalized to 896 x 896 resolution and encoded to 256 tokens each Total input context of 128K tokens for the 4B, 12B, and 27B sizes, and 32K tokens for the 1B size Output: Generated text in response to the input, such as an answer to a question, analysis of image content, or a summary of a document Total output context of 8192 tokens Usage Below, there are some code snippets on how to get quickly started with running the model. First, install the Transformers library. Gemma 3 is supported starting from transformers 4.50.0. $ pip install -U transformers Then, copy the snippet from the section that is relevant for your use case. Running with the pipeline API With instruction-tuned models, you