ShieldGemma è un insieme di classificatori di sicurezza predefiniti, basati su istruzioni e con pesi aperti, basati sulla famiglia di modelli Gemma per determinare se il testo o le immagini violano un criterio di sicurezza in input e in output.
ShieldGemma è addestrato a identificare i principali danni in diversi modelli. Per ulteriori informazioni, consulta le schede dei modelli.
ShieldGemma 2 per la moderazione dei contenuti delle immagini: disponibile in 4B. Per ulteriori dettagli, consulta la scheda del modello.
ShieldGemma 1 per la moderazione dei contenuti di testo: disponibile in 2 miliardi, 9 miliardi e 27 miliardi di parametri, consente di bilanciare velocità, prestazioni e generalizzabilità in base alle tue esigenze in qualsiasi implementazione. Per ulteriori dettagli, consulta la scheda del modello.
[[["Facile da capire","easyToUnderstand","thumb-up"],["Il problema è stato risolto","solvedMyProblem","thumb-up"],["Altra","otherUp","thumb-up"]],[["Mancano le informazioni di cui ho bisogno","missingTheInformationINeed","thumb-down"],["Troppo complicato/troppi passaggi","tooComplicatedTooManySteps","thumb-down"],["Obsoleti","outOfDate","thumb-down"],["Problema di traduzione","translationIssue","thumb-down"],["Problema relativo a esempi/codice","samplesCodeIssue","thumb-down"],["Altra","otherDown","thumb-down"]],["Ultimo aggiornamento 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)."]]