Deploy and use the Exasol Transformers Extension (TE) for NLP inference inside Exasol with notebook-connector. Covers `initialize_te_extension`, `deploy_scripts`, `PYTHON3_TE` language-container activation SQL, Hugging Face model-installation workflows, and the current TE SQL UDF surface.
インストールする前に、エージェントに与えられる指示の中身を確認できます。
Trigger when the user mentions Transformers Extension, TE extension, initialize_te_extension, deploy_scripts, Hugging Face models in Exasol, TE UDF, PYTHON3_TE, or NLP inference inside Exasol.
This skill routes notebook-connector Transformers Extension tasks to the reference material that covers TE setup, activation, validation, and the current TE SQL UDF surface.
Use this skill after notebook-connector configuration already exists in the SCS (secure config store). If the required DB or BucketFS values are still missing, activate exasol-notebook-connector-config first.
Extension setup and model handling
initialize_te_extension, deploy_scripts, install_model, huggingface_tokenreferences/transformers-extension.mdSQL UDF usage and validation
TE_TEXT_GENERATION_UDF, TE_DELETE_MODEL_UDF, get_activation_sql, transformers sql udfreferences/transformers-extension.mdMultiple routes can apply. Load the reference before responding.
The secure config store must already contain complete DB and BucketFS values. If not, activate exasol-notebook-connector-config first.
db_host_name, db_port, db_user, db_password, db_schemabfs_host_name, bfs_port, bfs_service, bfs_bucket, bfs_user, bfs_passwordhuggingface_token for gated or private modelsValidate setup with the reference flow after loading
references/transformers-extension.md.
Success signals:
Expected failure mode:
まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
Top-level router for Exasol work. Use for any Exasol database, exapump, SQL, BucketFS, extension, integration, UDF, Script Language Container, or Exasol Personal setup task, then route to the narrowest specialized Exasol skill.
日本語の概要は準備中です。原文の説明を表示しています。
Exasol BucketFS file system management via the `exapump bucketfs` CLI. Covers listing, uploading, downloading, and deleting files and directories in BucketFS, the `bfsdefault` service and other bucket services, bucket structure, `bfs_*` profile settings, the `/buckets/<service>/<bucket>/<path>` UDF path, and staging JARs, models, and Script Language Containers for UDFs.
日本語の概要は準備中です。原文の説明を表示しています。
Use Exasol Cloud Storage Extension workflows for moving structured object-storage files through extension UDFs. Covers setup prerequisites, the fixed `CLOUD_STORAGE_EXTENSION.IMPORT_PATH` and `CLOUD_STORAGE_EXTENSION.EXPORT_PATH` entrypoints used with `FROM SCRIPT` and `INTO SCRIPT`, Parquet, Avro, ORC, and Delta files on S3, Google Cloud Storage, Azure Blob Storage, Azure Data Lake, HDFS, and Alluxio, connection-object credential patterns, and routing away from native IMPORT or EXPORT when the extension path is the right fit.
日本語の概要は準備中です。原文の説明を表示しています。
Exasol database interaction via the exapump CLI and Exasol SQL. Covers SQL queries and DML/DDL such as `SELECT`, `INSERT`, `UPDATE`, `DELETE`, `MERGE`, `CREATE TABLE`, `ALTER TABLE`, and `DROP TABLE`, `CREATE CONNECTION` connection objects without import or export intent, schema inspection, table design, `exapump sql` and `exapump profile`, query profiling, analytics, and Exasol-specific SQL behavior outside exasol-import and exasol-export.
日本語の概要は準備中です。原文の説明を表示しています。
Distributed machine learning, data mining, and iterative HPC with Exasol. Covers end-to-end ML pipelines (DISTRIBUTE BY + SET scripts + BucketFS), per-entity federated training with partial_fit and ctx.reset(), batch inference, map-reduce ensemble training, distributed ensemble and SON algorithm for frequent itemset mining (Apriori, FP-Growth, association rules, market-basket analysis), Lua execute script orchestration for iterative algorithms (k-means, SGD, gradient descent), scikit-learn model training, parallel hyperparameter search, per-entity forecasting, anomaly detection, model lifecycle in BucketFS (pickle/joblib/ONNX versioning), GPU acceleration via CUDA SLCs (PyTorch/TensorFlow/RAPIDS), and ML-specific performance tuning (skew, OOM, multi-pass chunking).
日本語の概要は準備中です。原文の説明を表示しています。
Use Exasol document-file virtual schemas for federated read-only access to object and file storage — S3, Google Cloud Storage, Azure Blob Storage, and Azure Data Lake Storage Gen2 document files. Covers document-file adapter family selection, the EDML `MAPPING` definition, `CREATE VIRTUAL SCHEMA` usage, refresh workflows, and query-side troubleshooting.
日本語の概要は準備中です。原文の説明を表示しています。