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Stefano Fiorucci PRO

anakin87

AI & ML interests

Contributing to Haystack LLM framework 🏗️. Language Models: orchestration, post-training, synthetic data...

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cocogold: training Marigold for text-grounded segmentation

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🛡️ AI Guardrails with Open Language Models - Tutorial 📓 https://haystack.deepset.ai/cookbook/safety_moderation_open_lms How do you ensure your AI application is safe from harmful or inappropriate user inputs? This is a core requirement for real-world AI deployments. Luckily, several open Language Models are built specifically for safety moderation. I've been exploring them and put together a hands-on tutorial using the Haystack framework to build your own AI guardrails. In the notebook, you'll learn how to use and customize: 🔹 Meta Llama Guard (via Hugging Face API) 🔹 IBM Granite Guardian (via Ollama), which can also evaluate RAG specific risk dimensions 🔹 Google ShieldGemma (via Ollama) 🔹 Nvidia NemoGuard models family, including a model for topic control You'll also see how to integrate content moderation into a 🔎 RAG pipeline.

reacted to andito's post with 👀 6 days ago

🧠👁️ Can AI visualize solutions? Humans often solve visual problems by sketching ideas in our minds. What if Vision-Language Models (VLMs) could do something similar, not by generating full images, but by using internal “mental sketches”? That’s the idea behind Mirage, a new framework that empowers VLMs to reason using latent visual tokens. Instead of just thinking in words, Mirage mixes in abstract visual representations that help the model solve complex tasks. These aren't photorealistic images. They're compact, internal representations optimized purely to support reasoning. 🔧 Mirage is trained in two phases: 1) Grounding: It learns to produce latent tokens anchored in real images. 2) Refinement: The model drops the images and learns to generate visual tokens on its own. 📈 And yes, it works! On challenging benchmarks like Visual Spatial Planning, Jigsaw puzzles, and Spatial Attention Tasks, Mirage clearly outperforms GPT-4o and other strong baselines. Smart sketches > empty words. By mimicking the way humans visualize solutions, Mirage gives AI a new kind of imagination, one that’s faster, more efficient, and more human-like. Kudos to the teams at UMass Amherst and MIT behind this exciting work. Check the paper: https://huggingface.co/papers/2506.17218

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🛡️ AI Guardrails with Open Language Models - Tutorial

📓 https://haystack.deepset.ai/cookbook/safety_moderation_open_lms

How do you ensure your AI application is safe from harmful or inappropriate user inputs?

This is a core requirement for real-world AI deployments. Luckily, several open Language Models are built specifically for safety moderation.

I've been exploring them and put together a hands-on tutorial using the Haystack framework to build your own AI guardrails.

In the notebook, you'll learn how to use and customize:
🔹 Meta Llama Guard (via Hugging Face API)
🔹 IBM Granite Guardian (via Ollama), which can also evaluate RAG specific risk dimensions
🔹 Google ShieldGemma (via Ollama)
🔹 Nvidia NemoGuard models family, including a model for topic control

You'll also see how to integrate content moderation into a 🔎 RAG pipeline.

View all Posts