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378.6
TFLOPS
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Chris Scott
getfit
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OpenPipe/Deductive-Reasoning-Qwen-32B
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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! 🚀💡
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getfit/QwQ-32B-FP8-Dynamic
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