Joseph [open/acc] Pollack's picture

Joseph [open/acc] Pollack

Tonic

AI & ML interests

🤖Making robots to help people learn things quicker 👩🏻‍🚀🚀

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Tonic's activity

reacted to prithivMLmods's post with 🔥 9 days ago
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Dropping an entire collection of Style Intermixing Adapters on StrangerZone HF — including Realism, Anime, Sketch, Texture-Rich 3D Experimentals, Automotive Concept Images, and LoRA models based on Flux.1, SD 3.5 Turbo/Large, Stable Diffusion XL 🎨

╰┈➤Collection :
➜ sketch : strangerzonehf/sketch-fav-675ba869c7ceaec7e652ee1c
➜ sketch2 : strangerzonehf/q-series-sketch-678e3503bf3a661758429717
➜ automotive : strangerzonehf/automotive-3d-675bb31a491d8c264d45d843
➜ texture 3d : strangerzonehf/flux-3dxl-engine-674833c14a001d5b1fdb5139
➜ super 3d : strangerzonehf/super-3d-engine-6743231d69f496df97addd2b
➜ style mix : strangerzonehf/mixer-engine-673582c9c5939d8aa5bf9533
➜ realism : strangerzonehf/realism-engine-67343495b6daf0fbdb904cc1

╰┈➤The Entire Collection :
➜ flux.1 : prithivMLmods/flux-lora-collections-66dd5908be2206cfaa8519be
➜ flux-ultimate-lora-collection : strangerzonehf/Flux-Ultimate-LoRA-Collection
➜ sd 3.5 large / turbo : prithivMLmods/sd-35-large-lora-671b39d7bc2e7f71a446b163
➜ sdxl : prithivMLmods/sdxl-dev-models-667803a6d5ac75b59110e527

╰┈➤Pages :
➜ page 1: strangerzonehf
➜ page 2: @prithivMLmods
➜ demo : prithivMLmods/FLUX-LoRA-DLC

.🤗
reacted to freddyaboulton's post with 🚀❤️🧠 about 2 months ago
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Privacy matters when talking to AI! 🔇

We've just added a microphone mute button to FastRTC in our latest update (v0.0.14). Now you control exactly what your LLM hears.

Plus lots more features in this release! Check them out:
https://github.com/freddyaboulton/fastrtc/releases/tag/0.0.14
replied to clem's post about 2 months ago
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i actually used this invitation code and using it now to do my weekend jobs , it's very sharp 👍🏻

reacted to jsulz's post with 👍 about 2 months ago
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If you haven't already, I strong recommend reading @chiphuyen 's AI Engineering https://www.goodreads.com/en/book/show/216848047-ai-engineering

It comes complete with a section on open source AI (of obvious interest to the crowd here) and more than one mention of the Hugging Face community 🤗

In my opinion, one of the best parts is that it is a compendium for seminal and cutting-edge AI resources, with nearly 250 arXiv papers cited. I've done my best to collect them all in a single place, organized by chapter and by order in which they appear in the book:
jsulz/ai-engineering-67c5abe02c8596b5c089934c

Happy reading 🤓
reacted to albertvillanova's post with 😎❤️ about 2 months ago
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🚀 Big news for AI agents! With the latest release of smolagents, you can now securely execute Python code in sandboxed Docker or E2B environments. 🦾🔒

Here's why this is a game-changer for agent-based systems: 🧵👇

1️⃣ Security First 🔐
Running AI agents in unrestricted Python environments is risky! With sandboxing, your agents are isolated, preventing unintended file access, network abuse, or system modifications.

2️⃣ Deterministic & Reproducible Runs 📦
By running agents in containerized environments, you ensure that every execution happens in a controlled and predictable setting—no more environment mismatches or dependency issues!

3️⃣ Resource Control & Limits 🚦
Docker and E2B allow you to enforce CPU, memory, and execution time limits, so rogue or inefficient agents don’t spiral out of control.

4️⃣ Safer Code Execution in Production 🏭
Deploy AI agents confidently, knowing that any generated code runs in an ephemeral, isolated environment, protecting your host machine and infrastructure.

5️⃣ Easy to Integrate 🛠️
With smolagents, you can simply configure your agent to use Docker or E2B as its execution backend—no need for complex security setups!

6️⃣ Perfect for Autonomous AI Agents 🤖
If your AI agents generate and execute code dynamically, this is a must-have to avoid security pitfalls while enabling advanced automation.

⚡ Get started now: https://github.com/huggingface/smolagents

What will you build with smolagents? Let us know! 🚀💡
reacted to as-cle-bert's post with ❤️ about 2 months ago
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I just released a fully automated evaluation framework for your RAG applications!📈

GitHub 👉 https://github.com/AstraBert/diRAGnosis
PyPi 👉 https://pypi.org/project/diragnosis/

It's called 𝐝𝐢𝐑𝐀𝐆𝐧𝐨𝐬𝐢𝐬 and is a lightweight framework that helps you 𝗱𝗶𝗮𝗴𝗻𝗼𝘀𝗲 𝘁𝗵𝗲 𝗽𝗲𝗿𝗳𝗼𝗿𝗺𝗮𝗻𝗰𝗲 𝗼𝗳 𝗟𝗟𝗠𝘀 𝗮𝗻𝗱 𝗿𝗲𝘁𝗿𝗶𝗲𝘃𝗮𝗹 𝗺𝗼𝗱𝗲𝗹𝘀 𝗶𝗻 𝗥𝗔𝗚 𝗮𝗽𝗽𝗹𝗶𝗰𝗮𝘁𝗶𝗼𝗻𝘀.

You can launch it as an application locally (it's Docker-ready!🐋) or, if you want more flexibility, you can integrate it in your code as a python package📦

The workflow is simple:
🧠 You choose your favorite LLM provider and model (supported, for now, are Mistral AI, Groq, Anthropic, OpenAI and Cohere)
🧠 You pick the embedding models provider and the embedding model you prefer (supported, for now, are Mistral AI, Hugging Face, Cohere and OpenAI)
📄 You prepare and provide your documents
⚙️ Documents are ingested into a Qdrant vector database and transformed into a synthetic question dataset with the help of LlamaIndex
📊 The LLM is evaluated for the faithfulness and relevancy of its retrieval-augmented answer to the questions
📊 The embedding model is evaluated for hit rate and mean reciprocal ranking (MRR) of the retrieved documents

And the cool thing is that all of this is 𝗶𝗻𝘁𝘂𝗶𝘁𝗶𝘃𝗲 𝗮𝗻𝗱 𝗰𝗼𝗺𝗽𝗹𝗲𝘁𝗲𝗹𝘆 𝗮𝘂𝘁𝗼𝗺𝗮𝘁𝗲𝗱: you plug it in, and it works!🔌⚡

Even cooler? This is all built on top of LlamaIndex and its integrations: no need for tons of dependencies or fancy workarounds🦙
And if you're a UI lover, Gradio and FastAPI are there to provide you a seamless backend-to-frontend experience🕶️

So now it's your turn: you can either get diRAGnosis from GitHub 👉 https://github.com/AstraBert/diRAGnosis
or just run a quick and painless:

uv pip install diragnosis


To get the package installed (lightning-fast) in your environment🏃‍♀️

Have fun and feel free to leave feedback and feature/integrations requests on GitHub issues✨
reacted to daavoo's post with ❤️👍 about 2 months ago
reacted to albertvillanova's post with 👍 about 2 months ago
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3985
🚀 New smolagents update: Safer Local Python Execution! 🦾🐍

With the latest release, we've added security checks to the local Python interpreter: every evaluation is now analyzed for dangerous builtins, modules, and functions. 🔒

Here's why this matters & what you need to know! 🧵👇

1️⃣ Why is local execution risky? ⚠️
AI agents that run arbitrary Python code can unintentionally (or maliciously) access system files, run unsafe commands, or exfiltrate data.

2️⃣ New Safety Layer in smolagents 🛡️
We now inspect every return value during execution:
✅ Allowed: Safe built-in types (e.g., numbers, strings, lists)
⛔ Blocked: Dangerous functions/modules (e.g., os.system, subprocess, exec, shutil)

3️⃣ Immediate Benefits 💡
- Prevent agents from accessing unsafe builtins
- Block unauthorized file or network access
- Reduce accidental security vulnerabilities

4️⃣ Security Disclaimer ⚠️
🚨 Despite these improvements, local Python execution is NEVER 100% safe. 🚨
If you need true isolation, use a remote sandboxed executor like Docker or E2B.

5️⃣ The Best Practice: Use Sandboxed Execution 🔐
For production-grade AI agents, we strongly recommend running code in a Docker or E2B sandbox to ensure complete isolation.

6️⃣ Upgrade Now & Stay Safe! 🚀
Check out the latest smolagents release and start building safer AI agents today.

🔗 https://github.com/huggingface/smolagents

What security measures do you take when running AI-generated code? Let’s discuss! 👇

#AI #smolagents #Python #Security
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reacted to clem's post with ❤️ about 2 months ago
replied to their post about 2 months ago
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sure you can , check the links in the demo and the codebase that is available with each :-)

posted an update about 2 months ago
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🙋🏻‍♂️Hey there folks,

Did you know that you can use ModernBERT to detect model hallucinations ?

Check out the Demo : Tonic/hallucination-test

See here for Medical Context Demo : MultiTransformer/tonic-discharge-guard

check out the model from KRLabs : KRLabsOrg/lettucedect-large-modernbert-en-v1

and the library they kindly open sourced for it : https://github.com/KRLabsOrg/LettuceDetect

👆🏻if you like this topic please contribute code upstream 🚀

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posted an update about 2 months ago
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Powered by KRLabsOrg/lettucedect-large-modernbert-en-v1 from KRLabsOrg.

Detect hallucinations in answers based on context and questions using ModernBERT with 8192-token context support!

### Model Details
- **Model Name**: [lettucedect-large-modernbert-en-v1]( KRLabsOrg/lettucedect-large-modernbert-en-v1)
- **Organization**: [KRLabsOrg]( KRLabsOrg )
- **Github**: [https://github.com/KRLabsOrg/LettuceDetect](https://github.com/KRLabsOrg/LettuceDetect)
- **Architecture**: ModernBERT (Large) with extended context support up to 8192 tokens
- **Task**: Token Classification / Hallucination Detection
- **Training Dataset**: [RagTruth]( wandb/RAGTruth-processed)
- **Language**: English
- **Capabilities**: Detects hallucinated spans in answers, provides confidence scores, and calculates average confidence across detected spans.

LettuceDetect excels at processing long documents to determine if an answer aligns with the provided context, making it a powerful tool for ensuring factual accuracy.
reacted to Locutusque's post with 👍🚀🔥🤗 2 months ago
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2851
🎉 Exciting news, everyone! I've just released **Thespis-Llama-3.1-8B**, a new language model designed for enhanced roleplaying! ✨️

It's built on Llama-3.1 and fine-tuned with a focus on Theory of Mind reasoning to create more believable and engaging characters. It even learned a few tricks on its own, like adding in-character thought processes! 🧠

Check it out here: Locutusque/Thespis-Llama-3.1-8B

Give it a try and let me know what you think! I'm especially interested in feedback on how well the characters stay in role and if the responses feel natural. Looking forward to seeing what amazing stories you create! ✍️