{"id":44726,"date":"2025-06-18T15:57:43","date_gmt":"2025-06-18T08:57:43","guid":{"rendered":"\/id\/tutorial\/?p=44726"},"modified":"2025-12-18T23:27:13","modified_gmt":"2025-12-18T16:27:13","slug":"panduan-ollama-cli","status":"publish","type":"post","link":"\/id\/tutorial\/panduan-ollama-cli","title":{"rendered":"Tutorial Ollama CLI: cara menjalankan Ollama melalui terminal"},"content":{"rendered":"<p>Ollama adalah tool canggih untuk menjalankan Large Language Model (LLM) secara lokal. Tool ini memudahkan para developer, data scientist, dan pengguna teknis untuk mengustomisasi LLM sesuai dengan kebutuhan spesifik mereka.<\/p><p>Meskipun Ollama bisa digunakan dengan GUI pihak ketiga seperti Open WebUI, Anda juga bisa menjalankannya melalui CLI (Command-Line Interface) untuk mendokumentasikan respons ke dalam file dan mengotomatiskan alur kerja menggunakan skrip.<\/p><p>Di tutorial ini, Anda akan mempelajari cara menggunakan Ollama melalui CLI, mulai dari perintah-perintah dasarnya, berinteraksi dengan LLM, hingga mengotomatiskan tugas dan meluncurkan model Anda sendiri. Yuk, simak panduannya di bawah ini!<\/p><h2 class=\"wp-block-heading\" id=\"h-cara-setting-ollama-di-cli\">Cara setting Ollama di CLI<\/h2><p>Sebelum menggunakan Ollama di CLI, pastikan Anda sudah berhasil menginstalnya di sistem. Lakukan verifikasi dengan membuka terminal dan menjalankan perintah berikut:<\/p><pre class=\"EnlighterJSRAW\" data-enlighter-language=\"generic\" data-enlighter-theme=\"\" data-enlighter-highlight=\"\" data-enlighter-linenumbers=\"\" data-enlighter-lineoffset=\"\" data-enlighter-title=\"\" data-enlighter-group=\"\">ollama --version<\/pre><p>Anda akan melihat output seperti ini:<\/p><div class=\"wp-block-image\">\n<figure data-wp-context='{\"imageId\":\"69f2d85f71e54\"}' data-wp-interactive=\"core\/image\" class=\"aligncenter size-large wp-lightbox-container\"><img decoding=\"async\" width=\"1024\" height=\"177\" data-wp-class--hide=\"state.isContentHidden\" data-wp-class--show=\"state.isContentVisible\" data-wp-init=\"callbacks.setButtonStyles\" data-wp-on-async--click=\"actions.showLightbox\" data-wp-on-async--load=\"callbacks.setButtonStyles\" data-wp-on-async-window--resize=\"callbacks.setButtonStyles\" src=\"https:\/\/imagedelivery.net\/LqiWLm-3MGbYHtFuUbcBtA\/wp-content\/uploads\/sites\/37\/2025\/06\/versi-ollama-di-terminal.png\/public\" alt=\"Output terminal yang menampilkan versi Ollama yang terinstal\" class=\"wp-image-44735\" srcset=\"https:\/\/imagedelivery.net\/LqiWLm-3MGbYHtFuUbcBtA\/wp-content\/uploads\/sites\/37\/2025\/06\/versi-ollama-di-terminal.png\/w=1024,fit=scale-down 1024w, https:\/\/imagedelivery.net\/LqiWLm-3MGbYHtFuUbcBtA\/wp-content\/uploads\/sites\/37\/2025\/06\/versi-ollama-di-terminal.png\/w=300,fit=scale-down 300w, https:\/\/imagedelivery.net\/LqiWLm-3MGbYHtFuUbcBtA\/wp-content\/uploads\/sites\/37\/2025\/06\/versi-ollama-di-terminal.png\/w=150,fit=scale-down 150w, https:\/\/imagedelivery.net\/LqiWLm-3MGbYHtFuUbcBtA\/wp-content\/uploads\/sites\/37\/2025\/06\/versi-ollama-di-terminal.png\/w=768,fit=scale-down 768w\" sizes=\"(max-width: 1024px) 100vw, 1024px\" \/><button class=\"lightbox-trigger\" type=\"button\" aria-haspopup=\"dialog\" aria-label=\"Enlarge\" data-wp-init=\"callbacks.initTriggerButton\" data-wp-on-async--click=\"actions.showLightbox\" data-wp-style--right=\"state.imageButtonRight\" data-wp-style--top=\"state.imageButtonTop\">\n\t\t\t<svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"12\" height=\"12\" fill=\"none\" viewbox=\"0 0 12 12\">\n\t\t\t\t<path fill=\"#fff\" d=\"M2 0a2 2 0 0 0-2 2v2h1.5V2a.5.5 0 0 1 .5-.5h2V0H2Zm2 10.5H2a.5.5 0 0 1-.5-.5V8H0v2a2 2 0 0 0 2 2h2v-1.5ZM8 12v-1.5h2a.5.5 0 0 0 .5-.5V8H12v2a2 2 0 0 1-2 2H8Zm2-12a2 2 0 0 1 2 2v2h-1.5V2a.5.5 0 0 0-.5-.5H8V0h2Z\"><\/path>\n\t\t\t<\/svg>\n\t\t<\/button><\/figure><\/div><p>Selanjutnya, pelajari beberapa perintah penting Ollama di bawah ini:<\/p><figure tabindex=\"0\" class=\"wp-block-table\"><table class=\"has-fixed-layout\"><tbody><tr><td><strong>Perintah<\/strong><\/td><td><strong>Deskripsi<\/strong><\/td><\/tr><tr><td><code data-enlighter-language=\"generic\" class=\"EnlighterJSRAW\">ollama serve<\/code><\/td><td>Memulai Ollama di sistem lokal Anda.<\/td><\/tr><tr><td><code data-enlighter-language=\"generic\" class=\"EnlighterJSRAW\">ollama create &lt;new_model&gt;<\/code><\/td><td>Membuat model baru dari model yang sudah ada untuk penyesuaian atau pelatihan.<\/td><\/tr><tr><td><code data-enlighter-language=\"generic\" class=\"EnlighterJSRAW\">ollama show &lt;model&gt;<\/code><\/td><td>Menampilkan detail tentang model tertentu, seperti konfigurasi dan tanggal rilis.<\/td><\/tr><tr><td><code data-enlighter-language=\"generic\" class=\"EnlighterJSRAW\">ollama run &lt;model&gt;<\/code><\/td><td>Menjalankan model yang ditentukan agar siap digunakan.<\/td><\/tr><tr><td><code data-enlighter-language=\"generic\" class=\"EnlighterJSRAW\">ollama pull &lt;model&gt;<\/code><\/td><td>Mendownload model yang ditentukan ke sistem Anda.<\/td><\/tr><tr><td><code data-enlighter-language=\"generic\" class=\"EnlighterJSRAW\">ollama list<\/code><\/td><td>Mencantumkan semua model yang sudah didownload.<\/td><\/tr><tr><td><code data-enlighter-language=\"generic\" class=\"EnlighterJSRAW\">ollama ps<\/code><\/td><td>Menampilkan model yang sedang berjalan.<\/td><\/tr><tr><td><code data-enlighter-language=\"generic\" class=\"EnlighterJSRAW\">ollama stop &lt;model&gt;<\/code><\/td><td>Menghentikan model yang sedang berjalan, sesuai yang ditentukan.<\/td><\/tr><tr><td><code data-enlighter-language=\"generic\" class=\"EnlighterJSRAW\">ollama rm &lt;model&gt;<\/code><\/td><td>Menghapus model dari sistem, sesuai yang ditentukan.<\/td><\/tr><\/tbody><\/table><\/figure><h2 class=\"wp-block-heading\" id=\"h-penggunaan-dasar-ollama-di-cli\">Penggunaan dasar Ollama di CLI<\/h2><p>Bagian ini akan membahas penggunaan utama Ollama CLI, mulai dari berinteraksi dengan model hingga menyimpan output ke dalam file.<\/p><h3 class=\"wp-block-heading\" id=\"h-menjalankan-llm\">Menjalankan LLM<\/h3><p>Untuk mulai menggunakan LLM di Ollama, Anda perlu mendownload model yang diinginkan terlebih dahulu menggunakan perintah <strong>pull<\/strong>. Sebagai contoh, untuk menggunakan model Llama <strong>3.2<\/strong>, jalankan perintah berikut:<\/p><pre class=\"EnlighterJSRAW\" data-enlighter-language=\"generic\" data-enlighter-theme=\"\" data-enlighter-highlight=\"\" data-enlighter-linenumbers=\"\" data-enlighter-lineoffset=\"\" data-enlighter-title=\"\" data-enlighter-group=\"\">ollama pull llama3.2<\/pre><p>Tunggu hingga download selesai. Lama prosesnya bisa berbeda-beda tergantung pada ukuran file model yang didownload.<\/p><p>\n\n\n<div class=\"protip\">\n                    <h4 class=\"title\">Tips berguna<\/h4>\n                    <p>Apabila tidak yakin model mana yang harus didownload, kunjungi <a href=\"https:\/\/ollama.com\/library\" target=\"_blank\" rel=\"noopener\">library model resmi Ollama<\/a>. Library ini menyediakan informasi penting untuk setiap model, termasuk opsi penyesuaian, dukungan bahasa, dan skenario penggunaan yang direkomendasikan.<\/p>\n                <\/div>\n\n\n\n<\/p><p>Setelah model berhasil didownload, Anda bisa langsung menjalankannya dengan prompt spesifik seperti berikut:<\/p><pre class=\"EnlighterJSRAW\" data-enlighter-language=\"generic\" data-enlighter-theme=\"\" data-enlighter-highlight=\"\" data-enlighter-linenumbers=\"\" data-enlighter-lineoffset=\"\" data-enlighter-title=\"\" data-enlighter-group=\"\">ollama run llama3.2 \"Explain the basics of machine learning.\"<\/pre><p>Output yang dihasilkan kira-kira akan seperti ini:<\/p><div class=\"wp-block-image\">\n<figure data-wp-context='{\"imageId\":\"69f2d85f73928\"}' data-wp-interactive=\"core\/image\" class=\"aligncenter size-full wp-lightbox-container\"><img decoding=\"async\" width=\"1024\" height=\"586\" data-wp-class--hide=\"state.isContentHidden\" data-wp-class--show=\"state.isContentVisible\" data-wp-init=\"callbacks.setButtonStyles\" data-wp-on-async--click=\"actions.showLightbox\" data-wp-on-async--load=\"callbacks.setButtonStyles\" data-wp-on-async-window--resize=\"callbacks.setButtonStyles\" src=\"https:\/\/imagedelivery.net\/LqiWLm-3MGbYHtFuUbcBtA\/wp-content\/uploads\/sites\/37\/2025\/06\/output-llama-3.2-di-terminal.png\/public\" alt=\"Terminal menampilkan respons model Ollama tentang machine learning.\" class=\"wp-image-44731\" srcset=\"https:\/\/imagedelivery.net\/LqiWLm-3MGbYHtFuUbcBtA\/wp-content\/uploads\/sites\/37\/2025\/06\/output-llama-3.2-di-terminal.png\/w=1024,fit=scale-down 1024w, https:\/\/imagedelivery.net\/LqiWLm-3MGbYHtFuUbcBtA\/wp-content\/uploads\/sites\/37\/2025\/06\/output-llama-3.2-di-terminal.png\/w=300,fit=scale-down 300w, https:\/\/imagedelivery.net\/LqiWLm-3MGbYHtFuUbcBtA\/wp-content\/uploads\/sites\/37\/2025\/06\/output-llama-3.2-di-terminal.png\/w=150,fit=scale-down 150w, https:\/\/imagedelivery.net\/LqiWLm-3MGbYHtFuUbcBtA\/wp-content\/uploads\/sites\/37\/2025\/06\/output-llama-3.2-di-terminal.png\/w=768,fit=scale-down 768w\" sizes=\"(max-width: 1024px) 100vw, 1024px\" \/><button class=\"lightbox-trigger\" type=\"button\" aria-haspopup=\"dialog\" aria-label=\"Enlarge\" data-wp-init=\"callbacks.initTriggerButton\" data-wp-on-async--click=\"actions.showLightbox\" data-wp-style--right=\"state.imageButtonRight\" data-wp-style--top=\"state.imageButtonTop\">\n\t\t\t<svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"12\" height=\"12\" fill=\"none\" viewbox=\"0 0 12 12\">\n\t\t\t\t<path fill=\"#fff\" d=\"M2 0a2 2 0 0 0-2 2v2h1.5V2a.5.5 0 0 1 .5-.5h2V0H2Zm2 10.5H2a.5.5 0 0 1-.5-.5V8H0v2a2 2 0 0 0 2 2h2v-1.5ZM8 12v-1.5h2a.5.5 0 0 0 .5-.5V8H12v2a2 2 0 0 1-2 2H8Zm2-12a2 2 0 0 1 2 2v2h-1.5V2a.5.5 0 0 0-.5-.5H8V0h2Z\"><\/path>\n\t\t\t<\/svg>\n\t\t<\/button><\/figure><\/div><p>Atau, jalankan model tanpa perintah untuk memulai sesi interaktif:<\/p><pre class=\"EnlighterJSRAW\" data-enlighter-language=\"generic\" data-enlighter-theme=\"\" data-enlighter-highlight=\"\" data-enlighter-linenumbers=\"\" data-enlighter-lineoffset=\"\" data-enlighter-title=\"\" data-enlighter-group=\"\">ollama run llama3.2<\/pre><p>Dalam mode ini, Anda bisa memberikan pertanyaan atau instruksi, lalu LLM akan menghasilkan respons. Anda juga bisa bertanya lebih lanjut untuk mendapatkan jawaban yang mendetail atau mengklarifikasi jawaban yang diberikan, seperti pada contoh prompt berikut:<\/p><pre class=\"EnlighterJSRAW\" data-enlighter-language=\"generic\" data-enlighter-theme=\"\" data-enlighter-highlight=\"\" data-enlighter-linenumbers=\"\" data-enlighter-lineoffset=\"\" data-enlighter-title=\"\" data-enlighter-group=\"\">Can you elaborate on how machine learning is used in the healthcare sector?<\/pre><p>Setelah selesai, ketik:<\/p><pre class=\"EnlighterJSRAW\" data-enlighter-language=\"generic\" data-enlighter-theme=\"\" data-enlighter-highlight=\"\" data-enlighter-linenumbers=\"\" data-enlighter-lineoffset=\"\" data-enlighter-title=\"\" data-enlighter-group=\"\">\/bye<\/pre><p>Sesi Anda akan diakhiri, dan Anda diarahkan kembali ke tampilan terminal biasa.<\/p><h3 class=\"wp-block-heading\" id=\"h-melatih-llm\">Melatih LLM<\/h3><p>Model open-source terlatih seperti <strong>Llama 3.2<\/strong> sebenarnya sudah cukup bagus untuk tugas-tugas umum, seperti membuat konten. Namun, model ini mungkin tidak selalu optimal untuk kebutuhan yang lebih spesifik. Untuk meningkatkan akurasi model terkait topik tertentu, Anda perlu melatihnya dengan data yang lebih relevan.<\/p><p>Perlu diingat bahwa LLM memiliki <strong>keterbatasan memori jangka pendek<\/strong>, yang berarti data pelatihannya hanya akan disimpan selama sesi percakapan aktif. Apabila Anda mengakhiri suatu sesi dan memulai yang baru, model ini tidak akan mengingat informasi pelatihan sebelumnya.<\/p><p>Untuk melatih model ini, mulai sesi interaktif lalu ketikkan perintah berikut:<\/p><pre class=\"EnlighterJSRAW\" data-enlighter-language=\"generic\" data-enlighter-theme=\"\" data-enlighter-highlight=\"\" data-enlighter-linenumbers=\"\" data-enlighter-lineoffset=\"\" data-enlighter-title=\"\" data-enlighter-group=\"\">Hey, I want you to learn about [topic]. Can I train you on this?<\/pre><p>Anda kemudian akan mendapatkan respons seperti di bawah ini:<\/p><div class=\"wp-block-image\">\n<figure data-wp-context='{\"imageId\":\"69f2d85f7511c\"}' data-wp-interactive=\"core\/image\" class=\"aligncenter size-large wp-lightbox-container\"><img decoding=\"async\" width=\"1024\" height=\"78\" data-wp-class--hide=\"state.isContentHidden\" data-wp-class--show=\"state.isContentVisible\" data-wp-init=\"callbacks.setButtonStyles\" data-wp-on-async--click=\"actions.showLightbox\" data-wp-on-async--load=\"callbacks.setButtonStyles\" data-wp-on-async-window--resize=\"callbacks.setButtonStyles\" src=\"https:\/\/imagedelivery.net\/LqiWLm-3MGbYHtFuUbcBtA\/wp-content\/uploads\/sites\/37\/2025\/06\/output-training-llama-3-2-terminal.png\/public\" alt=\"Terminal yang menampilkan respons model Ollama terhadap prompt pelatihan.\" class=\"wp-image-44738\" srcset=\"https:\/\/imagedelivery.net\/LqiWLm-3MGbYHtFuUbcBtA\/wp-content\/uploads\/sites\/37\/2025\/06\/output-training-llama-3-2-terminal.png\/w=1024,fit=scale-down 1024w, https:\/\/imagedelivery.net\/LqiWLm-3MGbYHtFuUbcBtA\/wp-content\/uploads\/sites\/37\/2025\/06\/output-training-llama-3-2-terminal.png\/w=300,fit=scale-down 300w, https:\/\/imagedelivery.net\/LqiWLm-3MGbYHtFuUbcBtA\/wp-content\/uploads\/sites\/37\/2025\/06\/output-training-llama-3-2-terminal.png\/w=150,fit=scale-down 150w, https:\/\/imagedelivery.net\/LqiWLm-3MGbYHtFuUbcBtA\/wp-content\/uploads\/sites\/37\/2025\/06\/output-training-llama-3-2-terminal.png\/w=768,fit=scale-down 768w\" sizes=\"(max-width: 1024px) 100vw, 1024px\" \/><button class=\"lightbox-trigger\" type=\"button\" aria-haspopup=\"dialog\" aria-label=\"Enlarge\" data-wp-init=\"callbacks.initTriggerButton\" data-wp-on-async--click=\"actions.showLightbox\" data-wp-style--right=\"state.imageButtonRight\" data-wp-style--top=\"state.imageButtonTop\">\n\t\t\t<svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"12\" height=\"12\" fill=\"none\" viewbox=\"0 0 12 12\">\n\t\t\t\t<path fill=\"#fff\" d=\"M2 0a2 2 0 0 0-2 2v2h1.5V2a.5.5 0 0 1 .5-.5h2V0H2Zm2 10.5H2a.5.5 0 0 1-.5-.5V8H0v2a2 2 0 0 0 2 2h2v-1.5ZM8 12v-1.5h2a.5.5 0 0 0 .5-.5V8H12v2a2 2 0 0 1-2 2H8Zm2-12a2 2 0 0 1 2 2v2h-1.5V2a.5.5 0 0 0-.5-.5H8V0h2Z\"><\/path>\n\t\t\t<\/svg>\n\t\t<\/button><\/figure><\/div><p>Setelah itu, berikan informasi dasar tentang topik Anda agar model ini bisa memahaminya dengan lebih baik:<\/p><div class=\"wp-block-image\">\n<figure data-wp-context='{\"imageId\":\"69f2d85f767ea\"}' data-wp-interactive=\"core\/image\" class=\"aligncenter size-full wp-lightbox-container\"><img decoding=\"async\" width=\"1024\" height=\"554\" data-wp-class--hide=\"state.isContentHidden\" data-wp-class--show=\"state.isContentVisible\" data-wp-init=\"callbacks.setButtonStyles\" data-wp-on-async--click=\"actions.showLightbox\" data-wp-on-async--load=\"callbacks.setButtonStyles\" data-wp-on-async-window--resize=\"callbacks.setButtonStyles\" src=\"https:\/\/imagedelivery.net\/LqiWLm-3MGbYHtFuUbcBtA\/wp-content\/uploads\/sites\/37\/2025\/06\/prompt-training-llama-32-di-terminal.png\/public\" alt=\"Terminal yang menampilkan prompt untuk tujuan pelatihan.\" class=\"wp-image-44732\" srcset=\"https:\/\/imagedelivery.net\/LqiWLm-3MGbYHtFuUbcBtA\/wp-content\/uploads\/sites\/37\/2025\/06\/prompt-training-llama-32-di-terminal.png\/w=1024,fit=scale-down 1024w, https:\/\/imagedelivery.net\/LqiWLm-3MGbYHtFuUbcBtA\/wp-content\/uploads\/sites\/37\/2025\/06\/prompt-training-llama-32-di-terminal.png\/w=300,fit=scale-down 300w, https:\/\/imagedelivery.net\/LqiWLm-3MGbYHtFuUbcBtA\/wp-content\/uploads\/sites\/37\/2025\/06\/prompt-training-llama-32-di-terminal.png\/w=150,fit=scale-down 150w, https:\/\/imagedelivery.net\/LqiWLm-3MGbYHtFuUbcBtA\/wp-content\/uploads\/sites\/37\/2025\/06\/prompt-training-llama-32-di-terminal.png\/w=768,fit=scale-down 768w\" sizes=\"(max-width: 1024px) 100vw, 1024px\" \/><button class=\"lightbox-trigger\" type=\"button\" aria-haspopup=\"dialog\" aria-label=\"Enlarge\" data-wp-init=\"callbacks.initTriggerButton\" data-wp-on-async--click=\"actions.showLightbox\" data-wp-style--right=\"state.imageButtonRight\" data-wp-style--top=\"state.imageButtonTop\">\n\t\t\t<svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"12\" height=\"12\" fill=\"none\" viewbox=\"0 0 12 12\">\n\t\t\t\t<path fill=\"#fff\" d=\"M2 0a2 2 0 0 0-2 2v2h1.5V2a.5.5 0 0 1 .5-.5h2V0H2Zm2 10.5H2a.5.5 0 0 1-.5-.5V8H0v2a2 2 0 0 0 2 2h2v-1.5ZM8 12v-1.5h2a.5.5 0 0 0 .5-.5V8H12v2a2 2 0 0 1-2 2H8Zm2-12a2 2 0 0 1 2 2v2h-1.5V2a.5.5 0 0 0-.5-.5H8V0h2Z\"><\/path>\n\t\t\t<\/svg>\n\t\t<\/button><\/figure><\/div><p>Untuk melanjutkan pelatihan dan memberikan lebih banyak informasi, mintalah model ini untuk mengajukan pertanyaan tentang topik Anda, misalnya:<\/p><pre class=\"EnlighterJSRAW\" data-enlighter-language=\"generic\" data-enlighter-theme=\"\" data-enlighter-highlight=\"\" data-enlighter-linenumbers=\"\" data-enlighter-lineoffset=\"\" data-enlighter-title=\"\" data-enlighter-group=\"\">Can you ask me a few questions about [topic] to help you understand it better?<\/pre><p>Setelah model memperoleh cukup informasi tentang topik yang dibahas, Anda bisa mengakhiri pelatihan, lalu melakukan uji coba untuk memastikan model bisa mengingat dan menerapkan pengetahuan yang baru dipelajari.<\/p><div class=\"wp-block-image\">\n<figure data-wp-context='{\"imageId\":\"69f2d85f77edf\"}' data-wp-interactive=\"core\/image\" class=\"aligncenter size-full wp-lightbox-container\"><img decoding=\"async\" width=\"1024\" height=\"551\" data-wp-class--hide=\"state.isContentHidden\" data-wp-class--show=\"state.isContentVisible\" data-wp-init=\"callbacks.setButtonStyles\" data-wp-on-async--click=\"actions.showLightbox\" data-wp-on-async--load=\"callbacks.setButtonStyles\" data-wp-on-async-window--resize=\"callbacks.setButtonStyles\" src=\"https:\/\/imagedelivery.net\/LqiWLm-3MGbYHtFuUbcBtA\/wp-content\/uploads\/sites\/37\/2025\/06\/respons-cepat-llama-3-2-di-terminal-tentang-fenomena-kecantikan.png\/public\" alt=\"menguji coba model apakah bisa mengingat pelatihan yang baru dipelajari.\" class=\"wp-image-44733\" srcset=\"https:\/\/imagedelivery.net\/LqiWLm-3MGbYHtFuUbcBtA\/wp-content\/uploads\/sites\/37\/2025\/06\/respons-cepat-llama-3-2-di-terminal-tentang-fenomena-kecantikan.png\/w=1024,fit=scale-down 1024w, https:\/\/imagedelivery.net\/LqiWLm-3MGbYHtFuUbcBtA\/wp-content\/uploads\/sites\/37\/2025\/06\/respons-cepat-llama-3-2-di-terminal-tentang-fenomena-kecantikan.png\/w=300,fit=scale-down 300w, https:\/\/imagedelivery.net\/LqiWLm-3MGbYHtFuUbcBtA\/wp-content\/uploads\/sites\/37\/2025\/06\/respons-cepat-llama-3-2-di-terminal-tentang-fenomena-kecantikan.png\/w=150,fit=scale-down 150w, https:\/\/imagedelivery.net\/LqiWLm-3MGbYHtFuUbcBtA\/wp-content\/uploads\/sites\/37\/2025\/06\/respons-cepat-llama-3-2-di-terminal-tentang-fenomena-kecantikan.png\/w=768,fit=scale-down 768w\" sizes=\"(max-width: 1024px) 100vw, 1024px\" \/><button class=\"lightbox-trigger\" type=\"button\" aria-haspopup=\"dialog\" aria-label=\"Enlarge\" data-wp-init=\"callbacks.initTriggerButton\" data-wp-on-async--click=\"actions.showLightbox\" data-wp-style--right=\"state.imageButtonRight\" data-wp-style--top=\"state.imageButtonTop\">\n\t\t\t<svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"12\" height=\"12\" fill=\"none\" viewbox=\"0 0 12 12\">\n\t\t\t\t<path fill=\"#fff\" d=\"M2 0a2 2 0 0 0-2 2v2h1.5V2a.5.5 0 0 1 .5-.5h2V0H2Zm2 10.5H2a.5.5 0 0 1-.5-.5V8H0v2a2 2 0 0 0 2 2h2v-1.5ZM8 12v-1.5h2a.5.5 0 0 0 .5-.5V8H12v2a2 2 0 0 1-2 2H8Zm2-12a2 2 0 0 1 2 2v2h-1.5V2a.5.5 0 0 0-.5-.5H8V0h2Z\"><\/path>\n\t\t\t<\/svg>\n\t\t<\/button><\/figure><\/div><h3 class=\"wp-block-heading\" id=\"h-menulis-prompt-dan-mendokumentasikan-respons\">Menulis prompt dan mendokumentasikan respons<\/h3><p>Dengan Ollama, Anda bisa meminta LLM untuk melakukan tugas menggunakan file, seperti meringkas teks atau menganalisis informasi. Hal sangat berguna untuk dokumen panjang, karena Anda tidak perlu menyalin dan menempelkan teks saat memberikan instruksi pada model ini.<\/p><p>Sebagai contoh, kalau Anda memiliki file bernama <strong>input.txt<\/strong> yang berisi informasi yang ingin Anda rangkum, jalankan perintah berikut:<\/p><pre class=\"EnlighterJSRAW\" data-enlighter-language=\"generic\" data-enlighter-theme=\"\" data-enlighter-highlight=\"\" data-enlighter-linenumbers=\"\" data-enlighter-lineoffset=\"\" data-enlighter-title=\"\" data-enlighter-group=\"\">ollama run llama3.2 \"Summarize the content of this file in 50 words.\" &lt; input.txt<\/pre><p>Model ini akan membaca isi file dan menghasilkan ringkasan:<\/p><div class=\"wp-block-image\">\n<figure data-wp-context='{\"imageId\":\"69f2d85f795a5\"}' data-wp-interactive=\"core\/image\" class=\"aligncenter size-large wp-lightbox-container\"><img decoding=\"async\" width=\"1024\" height=\"152\" data-wp-class--hide=\"state.isContentHidden\" data-wp-class--show=\"state.isContentVisible\" data-wp-init=\"callbacks.setButtonStyles\" data-wp-on-async--click=\"actions.showLightbox\" data-wp-on-async--load=\"callbacks.setButtonStyles\" data-wp-on-async-window--resize=\"callbacks.setButtonStyles\" src=\"https:\/\/imagedelivery.net\/LqiWLm-3MGbYHtFuUbcBtA\/wp-content\/uploads\/sites\/37\/2025\/06\/ringkasan-respons-llama-3-2-terminal.png\/public\" alt=\"Terminal menampilkan respons model Ollama terhadap ringkasan file TXT\" class=\"wp-image-44734\" srcset=\"https:\/\/imagedelivery.net\/LqiWLm-3MGbYHtFuUbcBtA\/wp-content\/uploads\/sites\/37\/2025\/06\/ringkasan-respons-llama-3-2-terminal.png\/w=1024,fit=scale-down 1024w, https:\/\/imagedelivery.net\/LqiWLm-3MGbYHtFuUbcBtA\/wp-content\/uploads\/sites\/37\/2025\/06\/ringkasan-respons-llama-3-2-terminal.png\/w=300,fit=scale-down 300w, https:\/\/imagedelivery.net\/LqiWLm-3MGbYHtFuUbcBtA\/wp-content\/uploads\/sites\/37\/2025\/06\/ringkasan-respons-llama-3-2-terminal.png\/w=150,fit=scale-down 150w, https:\/\/imagedelivery.net\/LqiWLm-3MGbYHtFuUbcBtA\/wp-content\/uploads\/sites\/37\/2025\/06\/ringkasan-respons-llama-3-2-terminal.png\/w=768,fit=scale-down 768w\" sizes=\"(max-width: 1024px) 100vw, 1024px\" \/><button class=\"lightbox-trigger\" type=\"button\" aria-haspopup=\"dialog\" aria-label=\"Enlarge\" data-wp-init=\"callbacks.initTriggerButton\" data-wp-on-async--click=\"actions.showLightbox\" data-wp-style--right=\"state.imageButtonRight\" data-wp-style--top=\"state.imageButtonTop\">\n\t\t\t<svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"12\" height=\"12\" fill=\"none\" viewbox=\"0 0 12 12\">\n\t\t\t\t<path fill=\"#fff\" d=\"M2 0a2 2 0 0 0-2 2v2h1.5V2a.5.5 0 0 1 .5-.5h2V0H2Zm2 10.5H2a.5.5 0 0 1-.5-.5V8H0v2a2 2 0 0 0 2 2h2v-1.5ZM8 12v-1.5h2a.5.5 0 0 0 .5-.5V8H12v2a2 2 0 0 1-2 2H8Zm2-12a2 2 0 0 1 2 2v2h-1.5V2a.5.5 0 0 0-.5-.5H8V0h2Z\"><\/path>\n\t\t\t<\/svg>\n\t\t<\/button><\/figure><\/div><p>Dengan Ollama, Anda juga bisa mencatat respons model ke dalam file sehingga lebih mudah ditinjau atau diedit lebih lanjut. Berikut contoh mengajukan pertanyaan kepada model ini dan menyimpan outputnya ke dalam file:<\/p><pre class=\"EnlighterJSRAW\" data-enlighter-language=\"generic\" data-enlighter-theme=\"\" data-enlighter-highlight=\"\" data-enlighter-linenumbers=\"\" data-enlighter-lineoffset=\"\" data-enlighter-title=\"\" data-enlighter-group=\"\">ollama run llama3.2 \"Tell me about renewable energy.\"&gt; output.txt<\/pre><p>Respons model akan disimpan dalam file dengan format <strong>.txt<\/strong>:<\/p><div class=\"wp-block-image\">\n<figure data-wp-context='{\"imageId\":\"69f2d85f7ac1f\"}' data-wp-interactive=\"core\/image\" class=\"aligncenter size-full wp-lightbox-container\"><img decoding=\"async\" width=\"1024\" height=\"341\" data-wp-class--hide=\"state.isContentHidden\" data-wp-class--show=\"state.isContentVisible\" data-wp-init=\"callbacks.setButtonStyles\" data-wp-on-async--click=\"actions.showLightbox\" data-wp-on-async--load=\"callbacks.setButtonStyles\" data-wp-on-async-window--resize=\"callbacks.setButtonStyles\" src=\"https:\/\/imagedelivery.net\/LqiWLm-3MGbYHtFuUbcBtA\/wp-content\/uploads\/sites\/37\/2025\/06\/output-cat-terminal.png\/public\" alt=\"Terminal yang menampilkan isi file output.txt menggunakan perintah cat di Linux.\" class=\"wp-image-44730\" srcset=\"https:\/\/imagedelivery.net\/LqiWLm-3MGbYHtFuUbcBtA\/wp-content\/uploads\/sites\/37\/2025\/06\/output-cat-terminal.png\/w=1024,fit=scale-down 1024w, https:\/\/imagedelivery.net\/LqiWLm-3MGbYHtFuUbcBtA\/wp-content\/uploads\/sites\/37\/2025\/06\/output-cat-terminal.png\/w=300,fit=scale-down 300w, https:\/\/imagedelivery.net\/LqiWLm-3MGbYHtFuUbcBtA\/wp-content\/uploads\/sites\/37\/2025\/06\/output-cat-terminal.png\/w=150,fit=scale-down 150w, https:\/\/imagedelivery.net\/LqiWLm-3MGbYHtFuUbcBtA\/wp-content\/uploads\/sites\/37\/2025\/06\/output-cat-terminal.png\/w=768,fit=scale-down 768w\" sizes=\"(max-width: 1024px) 100vw, 1024px\" \/><button class=\"lightbox-trigger\" type=\"button\" aria-haspopup=\"dialog\" aria-label=\"Enlarge\" data-wp-init=\"callbacks.initTriggerButton\" data-wp-on-async--click=\"actions.showLightbox\" data-wp-style--right=\"state.imageButtonRight\" data-wp-style--top=\"state.imageButtonTop\">\n\t\t\t<svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"12\" height=\"12\" fill=\"none\" viewbox=\"0 0 12 12\">\n\t\t\t\t<path fill=\"#fff\" d=\"M2 0a2 2 0 0 0-2 2v2h1.5V2a.5.5 0 0 1 .5-.5h2V0H2Zm2 10.5H2a.5.5 0 0 1-.5-.5V8H0v2a2 2 0 0 0 2 2h2v-1.5ZM8 12v-1.5h2a.5.5 0 0 0 .5-.5V8H12v2a2 2 0 0 1-2 2H8Zm2-12a2 2 0 0 1 2 2v2h-1.5V2a.5.5 0 0 0-.5-.5H8V0h2Z\"><\/path>\n\t\t\t<\/svg>\n\t\t<\/button><\/figure><\/div><h2 class=\"wp-block-heading\" id=\"h-penggunaan-tingkat-lanjut-ollama-di-cli\">Penggunaan tingkat lanjut Ollama di CLI<\/h2><p>Setelah memahami penggunaan dasar Ollama di CLI, sekarang mari pelajari contoh penggunaan tingkat lanjut Ollama melalui CLI.<\/p><h3 class=\"wp-block-heading\" id=\"h-membuat-model-khusus\">Membuat model khusus<\/h3><p>Dengan menjalankan Ollama melalui CLI, Anda bisa membuat model khusus sesuai dengan kebutuhan spesifik Anda.<\/p><p>Untuk melakukannya, Anda perlu membuat Modelfile, yaitu blueprint model kustom Anda. File ini menentukan pengaturan utama seperti model dasar, parameter yang perlu disesuaikan, dan cara model akan merespons perintah.<\/p><p>Ikuti langkah-langkah berikut untuk membuat model kustom di Ollama:<\/p><p><strong>1. Buat Modelfile baru<\/strong><\/p><p>Gunakan editor teks seperti <a href=\"\/id\/tutorial\/cara-install-menggunakan-nano-text-editor\">nano<\/a><strong> <\/strong>untuk membuat Modelfile baru. Dalam contoh ini, kita akan menamai file dengan nama <strong>custom-modelfile<\/strong>:<\/p><pre class=\"EnlighterJSRAW\" data-enlighter-language=\"generic\" data-enlighter-theme=\"\" data-enlighter-highlight=\"\" data-enlighter-linenumbers=\"\" data-enlighter-lineoffset=\"\" data-enlighter-title=\"\" data-enlighter-group=\"\">nano custom-modelfile<\/pre><p>Selanjutnya, salin dan tempelkan template Modelfile dasar ini, yang akan kita sesuaikan di langkah berikutnya:<\/p><pre class=\"EnlighterJSRAW\" data-enlighter-language=\"generic\" data-enlighter-theme=\"\" data-enlighter-highlight=\"\" data-enlighter-linenumbers=\"\" data-enlighter-lineoffset=\"\" data-enlighter-title=\"\" data-enlighter-group=\"\"># Use Llama 3.2 as the base model\n\nFROM llama3.2\n\n# Adjust model parameters\n\nPARAMETER temperature 0.7\n\nPARAMETER num_ctx 3072\n\nPARAMETER stop \"assistant:\"\n\n# Define model behavior\n\nSYSTEM \"You are an expert in cyber security.\"\n\n# Customize the conversation template\n\nTEMPLATE \"\"\"{{ if .System }}Advisor: {{ .System }}{{ end }}\n\nClient: {{ .Prompt }}\n\nAdvisor: {{ .Response }}\"\"\"<\/pre><p><strong>2. Sesuaikan file Model<\/strong><\/p><p>Beberapa elemen penting yang bisa Anda sesuaikan dalam Modelfile antara lain:<\/p><ul class=\"wp-block-list\">\n<li><strong>Model dasar (FROM)<\/strong>. Menetapkan model dasar yang akan digunakan untuk instance khusus Anda. Misalnya, Anda bisa memilih Llama <strong>3.2<\/strong>:<\/li>\n<\/ul><pre class=\"EnlighterJSRAW\" data-enlighter-language=\"generic\" data-enlighter-theme=\"\" data-enlighter-highlight=\"\" data-enlighter-linenumbers=\"\" data-enlighter-lineoffset=\"\" data-enlighter-title=\"\" data-enlighter-group=\"\">FROM llama3.2<\/pre><ul class=\"wp-block-list\">\n<li><strong>Parameter (PARAMETER)<\/strong>. Mengatur perilaku model, seperti:\n<ul class=\"wp-block-list\">\n<li><strong>Temperature<\/strong>. Mengatur kreativitas model. Nilai lebih tinggi (misalnya <strong>1.0<\/strong>) membuat model lebih kreatif, sementara nilai lebih rendah (misalnya <strong>0.5<\/strong>) membuatnya lebih fokus.<\/li>\n<\/ul>\n<\/li>\n<\/ul><pre class=\"EnlighterJSRAW\" data-enlighter-language=\"generic\" data-enlighter-theme=\"\" data-enlighter-highlight=\"\" data-enlighter-linenumbers=\"\" data-enlighter-lineoffset=\"\" data-enlighter-title=\"\" data-enlighter-group=\"\">PARAMETER temperature 0.9<\/pre><ul class=\"wp-block-list\">\n<li><strong>Context window (num_ctx)<\/strong>. Menentukan berapa banyak teks sebelumnya yang digunakan sebagai konteks.<\/li>\n<\/ul><pre class=\"EnlighterJSRAW\" data-enlighter-language=\"generic\" data-enlighter-theme=\"\" data-enlighter-highlight=\"\" data-enlighter-linenumbers=\"\" data-enlighter-lineoffset=\"\" data-enlighter-title=\"\" data-enlighter-group=\"\">PARAMETER num_ctx 4096<\/pre><ul class=\"wp-block-list\">\n<li><strong>System message (SYSTEM)<\/strong>. Menentukan bagaimana model harus bertindak. Anda bisa memintanya untuk berperan sebagai karakter tertentu atau menghindari menjawab pertanyaan yang tidak relevan:<\/li>\n<\/ul><pre class=\"EnlighterJSRAW\" data-enlighter-language=\"generic\" data-enlighter-theme=\"\" data-enlighter-highlight=\"\" data-enlighter-linenumbers=\"\" data-enlighter-lineoffset=\"\" data-enlighter-title=\"\" data-enlighter-group=\"\">SYSTEM &ldquo;You are an expert in cyber security. Only answer questions related to cyber security. If asked anything unrelated, respond with: &lsquo;I only answer questions related to cyber security.&rsquo;\"<\/pre><ul class=\"wp-block-list\">\n<li><strong>Template (TEMPLATE).<\/strong> Menyesuaikan struktur interaksi antara pengguna dan model. Misalnya:<\/li>\n<\/ul><pre class=\"EnlighterJSRAW\" data-enlighter-language=\"generic\" data-enlighter-theme=\"\" data-enlighter-highlight=\"\" data-enlighter-linenumbers=\"\" data-enlighter-lineoffset=\"\" data-enlighter-title=\"\" data-enlighter-group=\"\">TEMPLATE \"\"\"{{ if .System }}&lt;|start|&gt;system\n\n{{ .System }}&lt;|end|&gt;{{ end }}\n\n&lt;|start|&gt;user\n\n{{ .Prompt }}&lt;|end|&gt;\n\n&lt;|start|&gt;assistant\n\n\"\"\"<\/pre><p>Setelah selesai melakukan penyesuaian, simpan file dan keluar dari nano dengan menekan <strong>Ctrl<\/strong> + <strong>X<\/strong>, lalu tekan <strong>Y<\/strong>, dan tekan <strong>Enter<\/strong>.<\/p><p><strong>3. Buat dan jalankan model khusus<\/strong><\/p><p>Setelah <strong>Modelfile<\/strong> siap, gunakan perintah di bawah ini untuk membuat model berdasarkan file tersebut:<\/p><pre class=\"EnlighterJSRAW\" data-enlighter-language=\"generic\" data-enlighter-theme=\"\" data-enlighter-highlight=\"\" data-enlighter-linenumbers=\"\" data-enlighter-lineoffset=\"\" data-enlighter-title=\"\" data-enlighter-group=\"\">ollama create custom-model-name -f .\/custom-modelfile<\/pre><p>Anda akan melihat output yang menunjukkan bahwa model berhasil dibuat.<\/p><div class=\"wp-block-image\">\n<figure data-wp-context='{\"imageId\":\"69f2d85f7c8ca\"}' data-wp-interactive=\"core\/image\" class=\"aligncenter size-full wp-lightbox-container\"><img decoding=\"async\" width=\"1024\" height=\"235\" data-wp-class--hide=\"state.isContentHidden\" data-wp-class--show=\"state.isContentVisible\" data-wp-init=\"callbacks.setButtonStyles\" data-wp-on-async--click=\"actions.showLightbox\" data-wp-on-async--load=\"callbacks.setButtonStyles\" data-wp-on-async-window--resize=\"callbacks.setButtonStyles\" src=\"https:\/\/imagedelivery.net\/LqiWLm-3MGbYHtFuUbcBtA\/wp-content\/uploads\/sites\/37\/2025\/06\/berhasil-membuat-model-kustom-ollama.png\/public\" alt=\"Output terminal menunjukkan proses pembuatan model kustom yang berhasil.\" class=\"wp-image-44729\" srcset=\"https:\/\/imagedelivery.net\/LqiWLm-3MGbYHtFuUbcBtA\/wp-content\/uploads\/sites\/37\/2025\/06\/berhasil-membuat-model-kustom-ollama.png\/w=1024,fit=scale-down 1024w, https:\/\/imagedelivery.net\/LqiWLm-3MGbYHtFuUbcBtA\/wp-content\/uploads\/sites\/37\/2025\/06\/berhasil-membuat-model-kustom-ollama.png\/w=300,fit=scale-down 300w, https:\/\/imagedelivery.net\/LqiWLm-3MGbYHtFuUbcBtA\/wp-content\/uploads\/sites\/37\/2025\/06\/berhasil-membuat-model-kustom-ollama.png\/w=150,fit=scale-down 150w, https:\/\/imagedelivery.net\/LqiWLm-3MGbYHtFuUbcBtA\/wp-content\/uploads\/sites\/37\/2025\/06\/berhasil-membuat-model-kustom-ollama.png\/w=768,fit=scale-down 768w\" sizes=\"(max-width: 1024px) 100vw, 1024px\" \/><button class=\"lightbox-trigger\" type=\"button\" aria-haspopup=\"dialog\" aria-label=\"Enlarge\" data-wp-init=\"callbacks.initTriggerButton\" data-wp-on-async--click=\"actions.showLightbox\" data-wp-style--right=\"state.imageButtonRight\" data-wp-style--top=\"state.imageButtonTop\">\n\t\t\t<svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"12\" height=\"12\" fill=\"none\" viewbox=\"0 0 12 12\">\n\t\t\t\t<path fill=\"#fff\" d=\"M2 0a2 2 0 0 0-2 2v2h1.5V2a.5.5 0 0 1 .5-.5h2V0H2Zm2 10.5H2a.5.5 0 0 1-.5-.5V8H0v2a2 2 0 0 0 2 2h2v-1.5ZM8 12v-1.5h2a.5.5 0 0 0 .5-.5V8H12v2a2 2 0 0 1-2 2H8Zm2-12a2 2 0 0 1 2 2v2h-1.5V2a.5.5 0 0 0-.5-.5H8V0h2Z\"><\/path>\n\t\t\t<\/svg>\n\t\t<\/button><\/figure><\/div><p>Setelah itu, jalankan model seperti biasa:<\/p><pre class=\"EnlighterJSRAW\" data-enlighter-language=\"generic\" data-enlighter-theme=\"\" data-enlighter-highlight=\"\" data-enlighter-linenumbers=\"\" data-enlighter-lineoffset=\"\" data-enlighter-title=\"\" data-enlighter-group=\"\">ollama run custom-model-name<\/pre><p>Langkah ini akan memulai model dengan semua penyesuaian yang telah Anda terapkan, dan Anda bisa langsung berinteraksi dengannya:<\/p><div class=\"wp-block-image\">\n<figure data-wp-context='{\"imageId\":\"69f2d85f7e4dd\"}' data-wp-interactive=\"core\/image\" class=\"aligncenter size-large wp-lightbox-container\"><img decoding=\"async\" width=\"1024\" height=\"135\" data-wp-class--hide=\"state.isContentHidden\" data-wp-class--show=\"state.isContentVisible\" data-wp-init=\"callbacks.setButtonStyles\" data-wp-on-async--click=\"actions.showLightbox\" data-wp-on-async--load=\"callbacks.setButtonStyles\" data-wp-on-async-window--resize=\"callbacks.setButtonStyles\" src=\"https:\/\/imagedelivery.net\/LqiWLm-3MGbYHtFuUbcBtA\/wp-content\/uploads\/sites\/37\/2025\/06\/respons-model-kustom-terminal.png\/public\" alt=\"Terminal menampilkan respons model kustom terhadap topik yang tidak terkait.\" class=\"wp-image-44739\" srcset=\"https:\/\/imagedelivery.net\/LqiWLm-3MGbYHtFuUbcBtA\/wp-content\/uploads\/sites\/37\/2025\/06\/respons-model-kustom-terminal.png\/w=1024,fit=scale-down 1024w, https:\/\/imagedelivery.net\/LqiWLm-3MGbYHtFuUbcBtA\/wp-content\/uploads\/sites\/37\/2025\/06\/respons-model-kustom-terminal.png\/w=300,fit=scale-down 300w, https:\/\/imagedelivery.net\/LqiWLm-3MGbYHtFuUbcBtA\/wp-content\/uploads\/sites\/37\/2025\/06\/respons-model-kustom-terminal.png\/w=150,fit=scale-down 150w, https:\/\/imagedelivery.net\/LqiWLm-3MGbYHtFuUbcBtA\/wp-content\/uploads\/sites\/37\/2025\/06\/respons-model-kustom-terminal.png\/w=768,fit=scale-down 768w\" sizes=\"(max-width: 1024px) 100vw, 1024px\" \/><button class=\"lightbox-trigger\" type=\"button\" aria-haspopup=\"dialog\" aria-label=\"Enlarge\" data-wp-init=\"callbacks.initTriggerButton\" data-wp-on-async--click=\"actions.showLightbox\" data-wp-style--right=\"state.imageButtonRight\" data-wp-style--top=\"state.imageButtonTop\">\n\t\t\t<svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"12\" height=\"12\" fill=\"none\" viewbox=\"0 0 12 12\">\n\t\t\t\t<path fill=\"#fff\" d=\"M2 0a2 2 0 0 0-2 2v2h1.5V2a.5.5 0 0 1 .5-.5h2V0H2Zm2 10.5H2a.5.5 0 0 1-.5-.5V8H0v2a2 2 0 0 0 2 2h2v-1.5ZM8 12v-1.5h2a.5.5 0 0 0 .5-.5V8H12v2a2 2 0 0 1-2 2H8Zm2-12a2 2 0 0 1 2 2v2h-1.5V2a.5.5 0 0 0-.5-.5H8V0h2Z\"><\/path>\n\t\t\t<\/svg>\n\t\t<\/button><\/figure><\/div><p>Anda bisa terus menyempurnakan Modelfile dengan mengubah parameter, mengedit pesan sistem, menambah template yang lebih canggih, atau bahkan menyertakan data Anda sendiri. Setelah itu, simpan perubahan dan jalankan kembali model untuk melihat efek dari perubahan yang dilakukan.<\/p><h3 class=\"wp-block-heading\" id=\"h-mengotomatiskan-tugas-dengan-skrip\">Mengotomatiskan tugas dengan skrip<\/h3><p>Mengotomatiskan tugas yang berulang di Ollama bisa menghemat waktu dan meningkatkan konsistensi alur kerja Anda. Dalam hal ini, gunakan bash script untuk menjalankan perintah secara otomatis, atau gunakan cron job untuk menjadwalkan tugas agar dijalankan pada waktu tertentu. Berikut caranya:<\/p><p><strong>Buat dan jalankan bash script<\/strong><\/p><p>Anda bisa <a href=\"\/id\/tutorial\/bash-script\">membuat bash script<\/a> yang menjalankan perintah Ollama. Berikut caranya:<\/p><ol class=\"wp-block-list\">\n<li>Buka editor teks dan buat file baru bernama <strong>ollama-script.sh<\/strong>:<\/li>\n<\/ol><pre class=\"EnlighterJSRAW\" data-enlighter-language=\"generic\" data-enlighter-theme=\"\" data-enlighter-highlight=\"\" data-enlighter-linenumbers=\"\" data-enlighter-lineoffset=\"\" data-enlighter-title=\"\" data-enlighter-group=\"\">nano ollama-script.sh<\/pre><ol start=\"2\" class=\"wp-block-list\">\n<li>Tambahkan perintah Ollama yang diperlukan. Misalnya, untuk menjalankan model dan menyimpan output ke sebuah file:<\/li>\n<\/ol><pre class=\"EnlighterJSRAW\" data-enlighter-language=\"generic\" data-enlighter-theme=\"\" data-enlighter-highlight=\"\" data-enlighter-linenumbers=\"\" data-enlighter-lineoffset=\"\" data-enlighter-title=\"\" data-enlighter-group=\"\">#!\/bin\/bash\n\n# Run the model and save the output to a file\n\nollama run llama3.2 \"What are the latest trends in AI?\" &gt; ai-output.txt<\/pre><ol start=\"3\" class=\"wp-block-list\">\n<li>Agar skrip dapat dieksekusi, berikan izin yang sesuai: <a href=\"\/id\/tutorial\/pengertian-chmod-dan-chown-untuk-permission-di-linux\">memberikan izin yang benar<\/a>:<\/li>\n<\/ol><pre class=\"EnlighterJSRAW\" data-enlighter-language=\"generic\" data-enlighter-theme=\"\" data-enlighter-highlight=\"\" data-enlighter-linenumbers=\"\" data-enlighter-lineoffset=\"\" data-enlighter-title=\"\" data-enlighter-group=\"\">chmod +x ollama-script.sh<\/pre><ol start=\"4\" class=\"wp-block-list\">\n<li>Jalankan skrip langsung dari terminal:<\/li>\n<\/ol><pre class=\"EnlighterJSRAW\" data-enlighter-language=\"generic\" data-enlighter-theme=\"\" data-enlighter-highlight=\"\" data-enlighter-linenumbers=\"\" data-enlighter-lineoffset=\"\" data-enlighter-title=\"\" data-enlighter-group=\"\">.\/ollama-script.sh<\/pre><p><strong>Atur cron job untuk mengotomatiskan tugas<\/strong><\/p><p>Anda juga bisa menggabungkan skrip ini dengan <a href=\"\/id\/tutorial\/cron-job\">cron job<\/a> untuk menjadwalkan tugas agar dijalankan secara otomatis. Berikut cara mengatur cron job untuk menjalankan skrip Ollama pada waktu tertentu:<\/p><ol class=\"wp-block-list\">\n<li>Buka editor crontab dengan mengetik:<\/li>\n<\/ol><pre class=\"EnlighterJSRAW\" data-enlighter-language=\"generic\" data-enlighter-theme=\"\" data-enlighter-highlight=\"\" data-enlighter-linenumbers=\"\" data-enlighter-lineoffset=\"\" data-enlighter-title=\"\" data-enlighter-group=\"\">crontab -e<\/pre><ol start=\"2\" class=\"wp-block-list\">\n<li>Tambahkan baris yang menentukan jadwal dan skrip yang ingin dijalankan. Misalnya, untuk menjalankan skrip setiap hari Minggu pada tengah malam:<\/li>\n<\/ol><pre class=\"EnlighterJSRAW\" data-enlighter-language=\"generic\" data-enlighter-theme=\"\" data-enlighter-highlight=\"\" data-enlighter-linenumbers=\"\" data-enlighter-lineoffset=\"\" data-enlighter-title=\"\" data-enlighter-group=\"\">0 0 * * 0 \/path\/to\/ollama-script.sh<\/pre><ol start=\"3\" class=\"wp-block-list\">\n<li>Simpan dan keluar dari editor setelah menambahkan cron job.<\/li>\n<\/ol><h2 class=\"wp-block-heading\" id=\"h-contoh-penggunaan-umum-untuk-cli\">Contoh penggunaan umum untuk CLI<\/h2><p>Berikut beberapa contoh penggunaan Ollama di CLI yang bisa Anda terapkan dalam berbagai kasus.<\/p><p><strong>Pembuatan teks<\/strong><\/p><p>Dengan menggunakan model yang sudah dilatih, Anda bisa membuat rangkuman, menghasilkan konten, atau menjawab pertanyaan tertentu.<\/p><ul class=\"wp-block-list\">\n<li>Meringkas file teks yang besar:<\/li>\n<\/ul><pre class=\"EnlighterJSRAW\" data-enlighter-language=\"generic\" data-enlighter-theme=\"\" data-enlighter-highlight=\"\" data-enlighter-linenumbers=\"\" data-enlighter-lineoffset=\"\" data-enlighter-title=\"\" data-enlighter-group=\"\">ollama run llama3.2 \"Summarize the following text:\" &lt; long-document.txt<\/pre><ul class=\"wp-block-list\">\n<li>Menghasilkan konten seperti postingan blog atau deskripsi produk:<\/li>\n<\/ul><pre class=\"EnlighterJSRAW\" data-enlighter-language=\"generic\" data-enlighter-theme=\"\" data-enlighter-highlight=\"\" data-enlighter-linenumbers=\"\" data-enlighter-lineoffset=\"\" data-enlighter-title=\"\" data-enlighter-group=\"\">ollama run llama3.2 \"Write a short article on the benefits of using AI in healthcare.\"&gt; article.txt<\/pre><ul class=\"wp-block-list\">\n<li>Menjawab pertanyaan spesifik untuk membantu penelitian:<\/li>\n<\/ul><pre class=\"EnlighterJSRAW\" data-enlighter-language=\"generic\" data-enlighter-theme=\"\" data-enlighter-highlight=\"\" data-enlighter-linenumbers=\"\" data-enlighter-lineoffset=\"\" data-enlighter-title=\"\" data-enlighter-group=\"\">ollama run llama3.2 \"What are the latest trends in AI, and how will they affect healthcare?\"<\/pre><p><strong>Pemrosesan, analisis, dan prediksi data<\/strong><\/p><p>Ollama juga memungkinkan Anda menangani berbagai tugas pemrosesan data, seperti klasifikasi teks, analisis sentimen, dan prediksi.<\/p><ul class=\"wp-block-list\">\n<li>Mengelompokkan teks ke dalam sentimen positif, negatif, atau netral:<\/li>\n<\/ul><pre class=\"EnlighterJSRAW\" data-enlighter-language=\"generic\" data-enlighter-theme=\"\" data-enlighter-highlight=\"\" data-enlighter-linenumbers=\"\" data-enlighter-lineoffset=\"\" data-enlighter-title=\"\" data-enlighter-group=\"\">ollama run llama3.2 \"Analyze the sentiment of this customer review: 'The product is fantastic, but delivery was slow.'\"<\/pre><ul class=\"wp-block-list\">\n<li>Mengategorikan teks ke dalam kategori yang telah ditentukan:<\/li>\n<\/ul><pre class=\"EnlighterJSRAW\" data-enlighter-language=\"generic\" data-enlighter-theme=\"\" data-enlighter-highlight=\"\" data-enlighter-linenumbers=\"\" data-enlighter-lineoffset=\"\" data-enlighter-title=\"\" data-enlighter-group=\"\">ollama run llama3.2 \"Classify this text into the following categories: News, Opinion, or Review.\" &lt; textfile.txt<\/pre><ul class=\"wp-block-list\">\n<li>Memprediksi hasil berdasarkan data yang disediakan:<\/li>\n<\/ul><pre class=\"EnlighterJSRAW\" data-enlighter-language=\"generic\" data-enlighter-theme=\"\" data-enlighter-highlight=\"\" data-enlighter-linenumbers=\"\" data-enlighter-lineoffset=\"\" data-enlighter-title=\"\" data-enlighter-group=\"\">ollama run llama3.2 \"Predict the stock price trend for the next month based on the following data:\" &lt; stock-data.txt<\/pre><p><strong>Integrasi dengan tool eksternal<\/strong><\/p><p>Penggunaan Ollama CLI juga mencakup integrasi dengan tool eksternal, memungkinkan Anda mengotomatiskan pemrosesan data dan meningkatkan kemampuan aplikasi lain.<\/p><ul class=\"wp-block-list\">\n<li>Mengintegrasikan Ollama dengan API pihak ketiga untuk mengambil data, memprosesnya, dan memberikan hasil:<\/li>\n<\/ul><pre class=\"EnlighterJSRAW\" data-enlighter-language=\"generic\" data-enlighter-theme=\"\" data-enlighter-highlight=\"\" data-enlighter-linenumbers=\"\" data-enlighter-lineoffset=\"\" data-enlighter-title=\"\" data-enlighter-group=\"\">curl -X GET \"https:\/\/api.example.com\/data\" | ollama run llama3.2 \"Analyze the following API data and summarize key insights.\"<\/pre><ul class=\"wp-block-list\">\n<li>Menggunakan kode Python untuk menjalankan subproses dengan Ollama:<\/li>\n<\/ul><pre class=\"EnlighterJSRAW\" data-enlighter-language=\"generic\" data-enlighter-theme=\"\" data-enlighter-highlight=\"\" data-enlighter-linenumbers=\"\" data-enlighter-lineoffset=\"\" data-enlighter-title=\"\" data-enlighter-group=\"\">import subprocess\n\nresult = subprocess.run(['ollama', 'run', 'llama3.2', 'Give me the latest stock market trends'], capture_output=True)\n\nprint(result.stdout.decode())<\/pre><figure class=\"wp-block-image size-large\"><a href=\"\/id\/hosting-vps\" target=\"_blank\" rel=\"noreferrer noopener\"><img decoding=\"async\" width=\"1024\" height=\"300\" src=\"https:\/\/imagedelivery.net\/LqiWLm-3MGbYHtFuUbcBtA\/wp-content\/uploads\/sites\/37\/2023\/02\/ID-VPS-hosting_in-text-banner.png\/public\" alt=\"\" class=\"wp-image-29630\" srcset=\"https:\/\/imagedelivery.net\/LqiWLm-3MGbYHtFuUbcBtA\/wp-content\/uploads\/sites\/37\/2023\/02\/ID-VPS-hosting_in-text-banner.png\/w=1024,fit=scale-down 1024w, https:\/\/imagedelivery.net\/LqiWLm-3MGbYHtFuUbcBtA\/wp-content\/uploads\/sites\/37\/2023\/02\/ID-VPS-hosting_in-text-banner.png\/w=300,fit=scale-down 300w, https:\/\/imagedelivery.net\/LqiWLm-3MGbYHtFuUbcBtA\/wp-content\/uploads\/sites\/37\/2023\/02\/ID-VPS-hosting_in-text-banner.png\/w=150,fit=scale-down 150w, https:\/\/imagedelivery.net\/LqiWLm-3MGbYHtFuUbcBtA\/wp-content\/uploads\/sites\/37\/2023\/02\/ID-VPS-hosting_in-text-banner.png\/w=768,fit=scale-down 768w\" sizes=\"(max-width: 1024px) 100vw, 1024px\" \/><\/a><\/figure><h2 class=\"wp-block-heading\" id=\"h-kesimpulan\"><strong>Kesimpulan<\/strong><\/h2><p>Melalui artikel ini, Anda sudah mempelajari berbagai hal penting dalam menggunakan Ollama melalui CLI, termasuk menjalankan perintah dasar, berinteraksi dengan model, dan menyimpan respons model ke dalam file.<\/p><p>Dengan CLI, Anda juga bisa melakukan tugas yang lebih canggih, seperti membuat model kustom, mengotomatiskan alur kerja dengan skrip dan cron job, serta mengintegrasikan Ollama dengan berbagai tool eksternal.<\/p><p>Setelah ini, Anda bisa mencoba berbagai fitur kustomisasi Ollama untuk memaksimalkan penggunaannya dalam proyek-proyek AI Anda. Apabila masih memiliki pertanyaan atau ingin berbagi pengalaman Anda menggunakan Ollama di CLI, jangan ragu untuk menyampaikannya lewat komentar, ya.<\/p><h2 class=\"wp-block-heading\" id=\"h-tanya-jawab-faq-tutorial-ollama-cli\">Tanya jawab (FAQ) tutorial Ollama CLI<\/h2><div id=\"rank-math-faq\" class=\"rank-math-block\">\n<div class=\"rank-math-list \">\n<div id=\"faq-question-69442b611402d\" class=\"rank-math-list-item\">\n<h3 class=\"rank-math-question \">Apa keuntungan menggunakan Ollama di CLI?<\/h3>\n<div class=\"rank-math-answer \">\n\n<p>Dengan menggunakan Ollama melalui CLI, Anda bisa menjalankan model, menghasilkan teks, melakukan pemrosesan data seperti analisis sentimen, mengotomatiskan alur kerja menggunakan skrip, membuat model kustom, dan mengintegrasikan Ollama dengan tool eksternal atau API untuk aplikasi tingkat lanjut.<\/p>\n\n<\/div>\n<\/div>\n<div id=\"faq-question-69442b6114031\" class=\"rank-math-list-item\">\n<h3 class=\"rank-math-question \">Bagaimana cara menginstal model untuk Ollama di CLI?<\/h3>\n<div class=\"rank-math-answer \">\n\n<p>Untuk menginstal model melalui CLI, pastikan Anda telah mendownload Ollama di sistem Anda. Setelah itu, gunakan perintah <strong>ollama pull<\/strong> diikuti dengan nama model. Contohnya, untuk menginstal Llama 3.2, jalankan:<strong> ollama pull llama3.2<\/strong>.<\/p>\n\n<\/div>\n<\/div>\n<div id=\"faq-question-69442b6114032\" class=\"rank-math-list-item\">\n<h3 class=\"rank-math-question \">Apakah bisa menggunakan model multimodal dalam versi CLI?<\/h3>\n<div class=\"rank-math-answer \">\n\n<p>Meskipun secara teknis Anda bisa menggunakan model multimodal seperti LlaVa di Ollama CLI, prosesnya mungkin agak repot karena CLI dioptimalkan untuk tugas-tugas berbasis teks. Anda bisa <a href=\"\/id\/tutorial\/panduan-ollama-gui\">menggunakan Ollama dengan tool GUI<\/a><strong> <\/strong>untuk menangani pekerjaan yang berhubungan dengan visual.<\/p>\n\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n","protected":false},"excerpt":{"rendered":"<p>Ollama adalah tool canggih untuk menjalankan Large Language Model (LLM) secara lokal. Tool ini memudahkan para developer, data scientist, dan pengguna teknis untuk mengustomisasi LLM sesuai dengan kebutuhan spesifik mereka. Meskipun Ollama bisa digunakan dengan GUI pihak ketiga seperti Open WebUI, Anda juga bisa menjalankannya melalui CLI (Command-Line Interface) untuk mendokumentasikan respons ke dalam file [&#8230;]<\/p>\n<p><a class=\"btn btn-secondary understrap-read-more-link\" href=\"\/id\/tutorial\/panduan-ollama-cli\">Read More&#8230;<\/a><\/p>\n","protected":false},"author":190,"featured_media":44727,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"rank_math_title":"Cara menjalankan Ollama melalui terminal (Ollama CLI)","rank_math_description":"Menggunakan Ollama dengan CLI memungkinkan Anda mendokumentasikan respons dan mengotomatiskan alur kerja. Baca tutorial Ollama CLI di sini!","rank_math_focus_keyword":"ollama cli","footnotes":""},"categories":[5096],"tags":[],"class_list":["post-44726","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-vps"],"hreflangs":[{"locale":"en-US","link":"https:\/\/www.hostinger.com\/tutorials\/ollama-cli-tutorial","default":0},{"locale":"fr-FR","link":"https:\/\/www.hostinger.com\/fr\/tutoriels\/tutoriel-ollama-cli","default":0},{"locale":"es-ES","link":"https:\/\/www.hostinger.com\/es\/tutoriales\/que-es-nslookup-3","default":0},{"locale":"id-ID","link":"https:\/\/www.hostinger.com\/id\/tutorial\/panduan-ollama-cli","default":0},{"locale":"en-UK","link":"https:\/\/www.hostinger.com\/uk\/tutorials\/ollama-cli-tutorial","default":0},{"locale":"en-MY","link":"https:\/\/www.hostinger.com\/my\/tutorials\/candle-business-name-ideas-9","default":0},{"locale":"en-PH","link":"https:\/\/www.hostinger.com\/ph\/tutorials\/ollama-cli-tutorial","default":0},{"locale":"en-IN","link":"https:\/\/www.hostinger.com\/in\/tutorials\/ollama-cli-tutorial","default":0},{"locale":"en-CA","link":"https:\/\/www.hostinger.com\/ca\/tutorials\/ollama-cli-tutorial","default":0},{"locale":"es-AR","link":"https:\/\/www.hostinger.com\/ar\/tutoriales\/que-es-nslookup-3","default":0},{"locale":"es-MX","link":"https:\/\/www.hostinger.com\/mx\/tutoriales\/que-es-nslookup-3","default":0},{"locale":"es-CO","link":"https:\/\/www.hostinger.com\/co\/tutoriales\/que-es-nslookup-3","default":0},{"locale":"en-AU","link":"https:\/\/www.hostinger.com\/au\/tutorials\/ollama-cli-tutorial","default":0},{"locale":"en-NG","link":"https:\/\/www.hostinger.com\/ng\/tutorials\/ollama-cli-tutorial","default":0}],"_links":{"self":[{"href":"https:\/\/www.hostinger.com\/id\/tutorial\/wp-json\/wp\/v2\/posts\/44726","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.hostinger.com\/id\/tutorial\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.hostinger.com\/id\/tutorial\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.hostinger.com\/id\/tutorial\/wp-json\/wp\/v2\/users\/190"}],"replies":[{"embeddable":true,"href":"https:\/\/www.hostinger.com\/id\/tutorial\/wp-json\/wp\/v2\/comments?post=44726"}],"version-history":[{"count":7,"href":"https:\/\/www.hostinger.com\/id\/tutorial\/wp-json\/wp\/v2\/posts\/44726\/revisions"}],"predecessor-version":[{"id":46993,"href":"https:\/\/www.hostinger.com\/id\/tutorial\/wp-json\/wp\/v2\/posts\/44726\/revisions\/46993"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.hostinger.com\/id\/tutorial\/wp-json\/wp\/v2\/media\/44727"}],"wp:attachment":[{"href":"https:\/\/www.hostinger.com\/id\/tutorial\/wp-json\/wp\/v2\/media?parent=44726"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.hostinger.com\/id\/tutorial\/wp-json\/wp\/v2\/categories?post=44726"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.hostinger.com\/id\/tutorial\/wp-json\/wp\/v2\/tags?post=44726"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}