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food ontrain
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🧮 Hash-code: 6f64d6fedcf1493b003f42a99e70c79d • 📆 2026-07-17 Verify Processor: high single-core performance needed RAM: enough space for background apps and [...]
food ontrain
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🔍 Hash-sum: e76da5e32ade12004e8575f3978f5b94 | 🕓 Last update: 2026-07-14 Verify Processor: Intel i7 / Ryzen 7 for heavy Quantized models [...]
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🔒 Hash checksum: 4bfe0be900fca036bbb15b5566238af6 • 📆 Last updated: 2026-07-11 Verify CPU: 8-core / 16-thread recommended for orchestration RAM: 64 [...]
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📎 HASH: 64f6693916e921effec5692ed38a5c5e | Updated: 2026-07-16 Verify Processor: 1 GHz dual-core required RAM: Minimum 4 GB Disk space: 64 [...]
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🧾 Hash-sum — ae38cc36c10e73bcfe44b6fddf70eca7 • 🗓 Updated on: 2026-07-13 Verify CPU: AVX2/AVX-512 instruction set required for llama.cpp RAM: 48 [...]
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🔍 Hash-sum: 4d840c785143c932b1370b2cea61fff7 | 🕓 Last update: 2026-07-12 Verify Processor: 4.0 GHz+ boost clock recommended for CPU inference RAM: [...]
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🛠 Hash code: c39a6f67cfed406f728a2eb795a8dee9 — Last modification: 2026-07-13 Verify Processor: 6-core 3.5 GHz minimum required RAM: 32 GB to [...]
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📄 Hash Value: e37e479f378db6a1710267464d71537a | 📆 Update: 2026-07-15 Verify CPU: 8-core / 16-thread recommended RAM: enough space for background [...]
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The fastest method for installing this model locally is by using Docker. Make sure you implement the steps mentioned [...]
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The fastest way to get this model running locally is via Optional Features. Make sure to follow the instructions [...]