The latest articles on DEV Community by Martial Terran (@martial_terran_6ecf247360). https://dev.to/martial_terran_6ecf247360 https://media2.dev.to/dynamic/image/width=90,height=90,fit=cover,gravity=auto,format=auto/https:%2F%2Fdev-to-uploads.s3.amazonaws.com%2Fuploads%2Fuser%2Fprofile_image%2F3567728%2Fe256e79a-3333-4881-81b9-28c3d3518935.png https://dev.to/martial_terran_6ecf247360 en Martial Terran Sat, 18 Oct 2025 05:43:30 +0000 https://dev.to/martial_terran_6ecf247360/if-you-have-a-website-favorite-webpage-try-this-app-to-see-how-it-might-rank-and-get-suggestions-3p2j https://dev.to/martial_terran_6ecf247360/if-you-have-a-website-favorite-webpage-try-this-app-to-see-how-it-might-rank-and-get-suggestions-3p2j <div class="ltag__link"> <a href="/pratham_naik_project_manager" class="ltag__link__link"> <div class="ltag__link__pic"> <img src="https://media2.dev.to/dynamic/image/width=800%2Cheight=%2Cfit=scale-down%2Cgravity=auto%2Cformat=auto/https%3A%2F%2Fdev-to-uploads.s3.amazonaws.com%2Fuploads%2Fuser%2Fprofile_image%2F2667579%2Feca818ae-fd03-4e29-8782-cc78cc40a86e.jpg" alt="pratham_naik_project_manager"> </div> </a> <a href="https://dev.to/pratham_naik_project_manager/i-built-an-eeat-checker-in-minutes-using-google-ai-studio-no-code-required-oo4" class="ltag__link__link"> <div class="ltag__link__content"> <h2>I Built an EEAT Checker in Minutes Using Google AI Studio (No Code Required)</h2> <h3>Pratham naik ・ Oct 14</h3> <div class="ltag__link__taglist"> <span class="ltag__link__tag">#deved</span> <span class="ltag__link__tag">#learngoogleaistudio</span> <span class="ltag__link__tag">#ai</span> <span class="ltag__link__tag">#gemini</span> </div> </div> </a> </div> deved learngoogleaistudio ai gemini Martial Terran Fri, 17 Oct 2025 05:31:32 +0000 https://dev.to/martial_terran_6ecf247360/artificial-hippocampus-networks-ahn-352a https://dev.to/martial_terran_6ecf247360/artificial-hippocampus-networks-ahn-352a <p>Learn about the new Artificial Hippocampus Networks (AHN) with my pure-PyTorch Qwen2-AHN model </p> <p><a href="https://media2.dev.to/dynamic/image/width=800%2Cheight=%2Cfit=scale-down%2Cgravity=auto%2Cformat=auto/https%3A%2F%2Fdev-to-uploads.s3.amazonaws.com%2Fuploads%2Farticles%2Fk435jz3o7a1j2ida629g.png" class="article-body-image-wrapper"><img src="https://media2.dev.to/dynamic/image/width=800%2Cheight=%2Cfit=scale-down%2Cgravity=auto%2Cformat=auto/https%3A%2F%2Fdev-to-uploads.s3.amazonaws.com%2Fuploads%2Farticles%2Fk435jz3o7a1j2ida629g.png" alt=" " width="800" height="800"></a></p> <p><a href="https://huggingface.co/MartialTerran/Toy_Qwen2-AHN_ByteDance-Seed_AHN" rel="noopener noreferrer">https://huggingface.co/MartialTerran/Toy_Qwen2-AHN_ByteDance-Seed_AHN</a></p> <p>Today I published a simplified educational version of the very complex Qwen2-AHN model. [I am developing a competing model architecture and wanted to study this one] The educational version Qwen2-AHN script is able to train on your custom dataset, and will generate a minimal vocab.json that fits your dataset, to reduce computational load. It runs on CPU or one GPU, in Google colab.</p> architecture python deeplearning llm