🔧 Digest: 4d1368c48b6b47b5ea5c3e256d14b039 • 🕒 Updated: 2026-07-19 Verify Processor: Intel i5 or AMD Ryzen 5 for basic 7B models RAM: […]

🧾 Hash-sum — 1871bd01ead6b02c9870328375ccac8e • 🗓 Updated on: 2026-07-17 Verify CPU: modern architecture (Zen 3 / Alder Lake minimum) RAM:

📤 Release Hash: b72635a9188fa406af8512073c2242bc • 📅 Date: 2026-07-13 Verify Processor: Intel i7 / Ryzen 7 for heavy Quantized models RAM:

📘 Build Hash: 14ae7425bcf5390ecc119150d562795e • 🗓 2026-07-17 Verify Processor: Intel i7 / Ryzen 7 for heavy Quantized models RAM: minimum

🔐 Hash sum: 61479a2d546d1069652df3dfd55565b4 | 📅 Last update: 2026-07-11 Verify CPU: multi-threading optimized for fast prompt processing RAM: 32 GB

💾 File hash: b5599d6bc861bde17569ba9f01aa2f4b (Update date: 2026-07-14) Verify CPU: multi-threading optimized for fast prompt processing RAM: 64 GB to avoid

🧾 Hash-sum — c4188e57a4f567d33b581bacba9ac1d4 • 🗓 Updated on: 2026-07-15 Verify CPU: AVX2/AVX-512 instruction set required for llama.cpp RAM: enough space

Running this model locally is fastest when deployed through a PowerShell script. Follow the guidelines below to continue. The process

The most efficient approach for a local installation is leveraging Docker containers. Simply follow the directions outlined below. Hands-free setup:

The fastest method for installing this model locally is by using Docker. Follow the guidelines below to continue. The installer