Tetap teratur dengan koleksi
Simpan dan kategorikan konten berdasarkan preferensi Anda.
Membuat model terjemahan kustom
Latih dan gunakan model terjemahan kustom menggunakan Google Cloud konsol. Contoh berikut menggunakan AutoML Translation untuk melatih model terjemahan bahasa Inggris-ke-Spanyol menggunakan set data yang berisi pasangan segmen yang berhubungan dengan teknologi yang diperoleh dari pelokalan software.
Sebelum memulai
Sebelum dapat mulai menggunakan AutoML Translation, project Anda harus mengaktifkan Cloud Translation API, dan Anda harus memiliki izin yang diberikan oleh peran berikut:
Peran Pelihat untuk melihat resource yang ada di project Anda
Peran Cloud Translation API Editor untuk membuat dan mengelola set data dan model
Peran Storage Admin untuk mengupload data pelatihan ke bucket Cloud Storage
Membuat set data terjemahan dan mengimpor pasangan segmen
Download file arsip yang berisi data sampel untuk melatih model, lalu ekstrak file.
Untuk tutorial ini, Anda akan menggunakan file TSV bahasa Inggris ke bahasa Spanyol.
Dari panel navigasi, klik Set Data untuk membuka halaman Set Data.
Klik Buat set data.
Di dialog Buat set data, tentukan detail tentang set data tersebut:
Masukkan tutorial_dataset sebagai nama set data.
Pilih Inggris (EN) sebagai bahasa sumber dari menu drop-down.
Pilih Spanyol (ES) sebagai target bahasa.
Klik Buat.
Setelah set data dibuat, klik nama set data untuk melihat detailnya.
Buka tab Impor, lalu upload set data en-es.tsv ke Cloud Storage:
Pilih Upload file dari komputer.
Klik Pilih file, lalu pilih file en-es.tsv yang telah
Anda download dan ekstrak sebelumnya.
Klik Jelajahi untuk memilih atau membuat bucket Cloud Storage baru tempat TSV disimpan. Region bucket harus us-central1.
Klik Lanjutkan.
AutoML Translation secara otomatis membagi data Anda menjadi set pelatihan, validasi, dan pengujian. Anda dapat melihat pemisahan ini dan pasangan kalimat
yang diimpor di tab Kalimat dari set data Anda.
Di bagian Evaluasi sebelumnya, Cloud Translation akan menampilkan skor BLEU model Anda jika dibandingkan dengan model Google NMT. Skor BLEU (Bilingual Evaluation
Understudy)
menunjukkan seberapa mirip teks kandidat dengan teks
referensi; nilai yang mendekati angka 100 mewakili teks yang lebih serupa.
Menggunakan model terjemahan
Dari Google Cloud konsol, Anda dapat menggunakan model kustom Anda untuk menerjemahkan beberapa
teks.
Di kotak teks Inggris, masukkan teks yang ingin diterjemahkan, lalu klik
Terjemahkan.
Anda dapat membandingkan hasil dari model kustom Anda dengan model Google NMT.
Pembersihan
Untuk menghindari tagihan yang tidak perlu, hapus model, set data, dan file en-es.tsv Anda. Google Cloud Anda juga dapat menggunakan
Google Cloud console untuk menghapus project Anda jika tidak membutuhkannya.
Langkah berikutnya
Untuk mempelajari model kustom, silakan melihat Panduan pemula.
Untuk membuat set data dan model kustom Anda sendiri, silakan melihat Menyiapkan data pelatihan untuk mendapatkan petunjuk tentang cara menyiapkan data.
[[["Mudah dipahami","easyToUnderstand","thumb-up"],["Memecahkan masalah saya","solvedMyProblem","thumb-up"],["Lainnya","otherUp","thumb-up"]],[["Sulit dipahami","hardToUnderstand","thumb-down"],["Informasi atau kode contoh salah","incorrectInformationOrSampleCode","thumb-down"],["Informasi/contoh yang saya butuhkan tidak ada","missingTheInformationSamplesINeed","thumb-down"],["Masalah terjemahan","translationIssue","thumb-down"],["Lainnya","otherDown","thumb-down"]],["Terakhir diperbarui pada 2025-09-09 UTC."],[],[],null,["# Create a custom translation model\n=================================\n\n| **Note:** Translation LLM can be customized with your training data using [Vertex AI supervised fine-tuning - Public Preview](/vertex-ai/generative-ai/docs/models/translation-supervised-tuning).\n\nTrain and use a custom translation model by using the Google Cloud console. The\nfollowing example uses AutoML Translation to train an English-to-Spanish\ntranslation model by using a dataset that contains technology-oriented segment\npairs from software localization.\n| **Note:** The following tutorial assumes that, for your project, the Google Cloud console is using the Cloud Translation API instead of the AutoML API to create datasets. This condition is true if you have at least one native Cloud Translation resource or no legacy AutoML resources in your project. If you have only legacy AutoML resources, see [Upgrade AutoML resources](/translate/docs/advanced/automl-upgrade) for more information.\n\nBefore you begin\n----------------\n\nBefore you can start using AutoML Translation, your project must have the\nCloud Translation API enabled, and you must have the permissions that are granted by\nthe following roles:\n\n- **Viewer** role to view existing resources in your project\n- **Cloud Translation API Editor** role to create and manage datasets and models\n- **Storage Admin** role to upload training data to a Cloud Storage bucket\n\nCreate a translation dataset and import segment pairs\n-----------------------------------------------------\n\n1. [Download](/static/translate/docs/advanced/sample/automl-translation-data.zip) the\n archive file that contains the sample data for training the model, and\n extract the files.\n\n For this tutorial, you'll use the English to Spanish TSV file.\n2. Go to the AutoML Translation console.\n\n [Go to the\n Translation page](https://console.cloud.google.com/translation)\n3. From the navigation pane, click **Datasets** to go to the **Datasets** page.\n\n4. Click **Create dataset**.\n\n5. In the **Create dataset** dialog, specify details about the dataset:\n\n 1. Enter `tutorial_dataset` as the name for the dataset.\n 2. Select **English (EN)** as your source language from the drop-down list.\n 3. Select **Spanish (ES)** as your target language.\n 4. Click **Create**.\n6. After the dataset is created, click the dataset name to view its details.\n\n7. Go to the **Import** tab and upload the `en-es.tsv` dataset to\n Cloud Storage:\n\n 1. Select **Upload files from your computer**.\n 2. Click **Select files** , and choose the `en-es.tsv` file that you previously downloaded and extracted.\n 3. Click **Browse** to select or create a new Cloud Storage bucket where your TSV is stored. The bucket region must be `us-central1`.\n8. Click **Continue**.\n\n AutoML Translation automatically splits your data into training,\n validation, and testing sets. You can view these splits and the imported\n sentence pairs in the **Sentences** tab of your dataset.\n\nTrain a model\n-------------\n\n1. Go to the AutoML Translation console.\n\n [Go to the\n Translation page](https://console.cloud.google.com/translation)\n2. From the navigation pane, go to the **Datasets** page.\n\n3. Click the **tutorial_dataset** dataset.\n\n4. Go to the **Train** tab.\n\n5. Click **Start training** , which opens the **Train new model** pane.\n\n6. Enter `tutorial_model` for the model name.\n\n7. Click **Start training**.\n\nTraining a model can take several hours to complete.\n\nEvaluate the model\n------------------\n\nCheck to see how the model compares to the default Google NMT model that is\nbased on segment pairs from your test set.\n\n1. Go to the AutoML Translation console.\n\n [Go to the\n Translation page](https://console.cloud.google.com/translation)\n2. From the navigation pane, go to the **Models** page.\n\n3. Click the **tutorial_model** model.\n\n4. Click the **Evaluate** tab.\n\nIn the **Previous evaluations** section, Cloud Translation shows your model's\nBLEU score compared to the Google NMT model. The [BLEU (Bilingual Evaluation\nUnderstudy)](/translate/docs/advanced/automl-evaluate#bleu)\nscore indicates how similar the candidate text is to the reference\ntexts; values closer to 100 represent more similar texts.\n\nUse the translation model\n-------------------------\n\nFrom the Google Cloud console, you can use your custom model to translate some\ntext.\n\n1. Go to the AutoML Translation console.\n\n [Go to the\n Translation page](https://console.cloud.google.com/translation)\n2. From the navigation pane, go to the **Models** page.\n\n3. Click the **tutorial_model** model.\n\n4. Click the **Predict** tab.\n\n5. In the **English** text box, enter text to translate and then click\n **Translate**.\n\n You can compare the results from your custom model to the Google NMT model.\n\nClean up\n--------\n\nTo avoid unnecessary Google Cloud charges, delete your [model](/translate/docs/advanced/automl-models#delete-model),\n[dataset](/translate/docs/advanced/automl-datasets#delete-dataset), and `en-es.tsv` file. You can also use the\n[Google Cloud console](https://console.cloud.google.com/) to delete your project if you don't need it.\n\nWhat's next\n-----------\n\n- To learn about custom models, see the [Beginner's guide](/translate/docs/advanced/automl-beginner).\n- To create your own dataset and custom model, see [Prepare training\n data](/translate/docs/advanced/automl-prepare) for instructions on how to prepare your data."]]
