Llama Guard 4 Released on Hugging Face Hub
Meta's Llama Guard 4 safety classifier has been made available on the Hugging Face Hub. Llama Guard 4 is a content moderation model designed to detect unsafe inputs and outputs in LLM pipelines. The Hugging Face blog post announces its availability and integration into the Hub ecosystem, continuing the Llama Guard series of safety-focused models.
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Meta releases Llama Guard 4 12B multimodal safety classifier on Hugging Face
Meta released Llama Guard 4 12B, a multimodal (image-text-to-text) safety classification model built on the Llama 4 architecture, published to Hugging Face. The model is designed for conversational safety filtering and supports both text and image inputs. With 143K downloads and 102 likes shortly after release, it is seeing meaningful early adoption.
Meta releases Llama Guard 3 1B safety classifier on Hugging Face
Meta released Llama Guard 3 1B, a compact 1-billion-parameter text-generation model designed for content safety classification, published on Hugging Face. The model is part of the Llama Guard 3 family and supports multiple languages including English, German, and French. Its small size makes it suitable for lightweight safety filtering in production deployments.
Meta releases Llama Guard 3 11B Vision for multimodal content safety classification
Meta released Llama Guard 3 11B Vision on Hugging Face, a multimodal safety classifier supporting image-text-to-text inputs built on the Llama 3 architecture. The model extends the Llama Guard safety classification family to handle visual content alongside text. This is relevant to AI safety tooling for multimodal deployments.
Meta releases Llama Prompt Guard 2 (22M) safety classifier on Hugging Face
Meta released Llama Prompt Guard 2-22M, a lightweight 22-million-parameter text classification model for prompt safety, published on Hugging Face under the meta-llama organization. The model is based on DeBERTa-v2 architecture and tagged for safety use cases including prompt injection and jailbreak detection. It is part of the Llama 4 safety tooling ecosystem and supports English and French.
Welcome Llama 4 Maverick & Scout on Hugging Face
Hugging Face announces the availability of Meta's Llama 4 Maverick and Scout models on its platform. These are the first models in Meta's new Llama 4 generation, representing a significant open-weights release. The post covers integration details, model access, and usage on the Hugging Face ecosystem.
Meta releases Llama Prompt Guard 2 (86M) for prompt injection and jailbreak detection
Meta released Llama Prompt Guard 2-86M, a DeBERTa-v2-based text classification model on Hugging Face designed for safety filtering, specifically prompt injection and jailbreak detection. The model is tagged with llama4, suggesting it is part of the Llama 4 safety tooling ecosystem. With over 122K downloads, it has seen meaningful early adoption.
Llama 3.2 in Keras
Hugging Face published a blog post detailing the integration of Meta's Llama 3.2 models into the Keras framework. The post covers how developers can use Keras to load, fine-tune, and run inference with Llama 3.2, expanding the ecosystem of tools available for working with the model. This represents a tooling/framework integration update rather than a new capability announcement.
Meta releases Llama 4 Scout 17B-16E instruct model on Hugging Face
Meta released Llama 4 Scout, a 17B active parameter / 16-expert mixture-of-experts instruct model with image-text-to-text (multimodal) capabilities, published on Hugging Face under the meta-llama organization. The model supports multiple languages including Arabic, German, and English. With over 420K downloads and 1,300 likes shortly after release, it is seeing significant community uptake.