ShieldGemma es un conjunto de clasificadores de seguridad de pesos abiertos, listos para usar y ajustados a las instrucciones, compilados en la familia de modelos de Gemma para determinar si el texto o las imágenes incumplen una política de seguridad en las entradas y salidas.
ShieldGemma está entrenado para identificar daños clave en diferentes modelos. Consulta las tarjetas de modelo para obtener más información.
ShieldGemma 2 para la moderación de contenido de imágenes: Disponible en 4B. Consulta la tarjeta de modelo para obtener más detalles.
ShieldGemma 1 para la moderación de contenido de texto: Disponible en 2B, 9B y 27B, lo que te permite equilibrar la velocidad, el rendimiento y la generalización para satisfacer tus necesidades en cualquier implementación. Consulta la tarjeta de modelo para obtener más detalles.
[[["Fácil de comprender","easyToUnderstand","thumb-up"],["Resolvió mi problema","solvedMyProblem","thumb-up"],["Otro","otherUp","thumb-up"]],[["Falta la información que necesito","missingTheInformationINeed","thumb-down"],["Muy complicado o demasiados pasos","tooComplicatedTooManySteps","thumb-down"],["Desactualizado","outOfDate","thumb-down"],["Problema de traducción","translationIssue","thumb-down"],["Problema con las muestras o los códigos","samplesCodeIssue","thumb-down"],["Otro","otherDown","thumb-down"]],["Última actualización: 2025-03-24 (UTC)"],[],[],null,["# ShieldGemma\n\n\u003cbr /\u003e\n\n[ShieldGemma](/gemma/docs/shieldgemma) is a set of ready-made, instruction-tuned, open\nweights safety classifiers built on the Gemma family of models to determine\nwhether text or images violate a safety policy across input and output.\nShieldGemma is trained to identify across key harms across different models, see\nthe model cards for more information.\n\n- ShieldGemma 2 for image content moderation: Available in 4B. See the [model card](/gemma/docs/shieldgemma/model_card_2) for more details.\n- ShieldGemma 1 for text content moderation: Available in 2B, 9B, and 27B---allowing you to balance speed, performance, and generalizability to suit your needs across any deployment. See the [model card](/gemma/docs/shieldgemma/model_card) for more details.\n\n| **Note:** While ShieldGemma is trained on key harms, it may be generalizable to other harms related to your use case. It's important to experiment and regularly assess how well ShieldGemma fits your needs.\n\n**Safeguard your models with ShieldGemma**\n\n|---|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| | [Image moderation: ShieldGemma 2 in Transformers](https://colab.research.google.com/github/google/generative-ai-docs/blob/main/site/en/responsible/docs/safeguards/shieldgemma2_on_huggingface.ipynb) | [Text moderation: ShieldGemma in Transformers](https://colab.research.google.com/github/google/generative-ai-docs/blob/main/site/en/responsible/docs/safeguards/shieldgemma_on_huggingface.ipynb) | [Text moderation: ShieldGemma in Keras](https://colab.research.google.com/github/google/generative-ai-docs/blob/main/site/en/responsible/docs/safeguards/shieldgemma_on_keras.ipynb) |\n\n\u003cbr /\u003e\n\nYou can use ShieldGemma models in the following frameworks.\n\n- [KerasNLP](https://keras.io/keras_nlp/), with model checkpoints available from [Kaggle](https://www.kaggle.com/search?q=shieldgemma+in%3Amodels).\n- [Hugging Face Transformers](https://github.com/huggingface/transformers), with model checkpoints available from [Hugging Face Hub](https://huggingface.co/collections/google/shieldgemma-release-66a20efe3c10ef2bd5808c79)."]]