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Found 6 Skills
Expert in Natural Language Processing, designing systems for text classification, NER, translation, and LLM integration using Hugging Face, spaCy, and LangChain. Use when building NLP pipelines, text analysis, or LLM-powered features. Triggers include "NLP", "text classification", "NER", "named entity", "sentiment analysis", "spaCy", "Hugging Face", "transformers".
Guidance for training FastText text classification models with constraints on model size and accuracy. This skill should be used when training FastText models, optimizing hyperparameters, or balancing trade-offs between model size and classification accuracy.
Deploy the Cortex CLASSIFY_TEXT tutorial notebook to the user's Snowflake account and provide a link to open it in Snowsight. Use when user wants to learn text classification through a Jupyter notebook experience.
Auto-sort, categorize, or label content using AI. Use when sorting tickets into categories, auto-tagging content, labeling emails, detecting sentiment, routing messages to the right team, triaging support requests, building a spam filter, intent detection, topic classification, or any task where text goes in and a category comes out.
Interactive tutorial teaching Snowflake Cortex CLASSIFY_TEXT for categorizing unstructured text. Guide users through classifying customer reviews using Python and SQL. Use when user wants to learn text classification, Cortex LLM functions, or analyze unstructured feedback data.
Get a fast, cheap, typed judgment over text or JSON from the jev CLI — a yes/no probability, one choice among labels, or an ordinal score — bare calibrated answers, never prose or explanations. Runs now from a shell or agent, in bulk (one decision per line) and in pipelines (exit codes, semantic grep). Use to classify, triage, route, screen, rank, filter or bulk-label items such as emails, customer feedback, chat or group messages, tweets, logs, git diffs or user requests, and as a cheap pre-filter before expensive LLM reading, a guardrail check, or a model/agent router. 适用：分类、筛选、分诊、路由、打分、是非判断、批量打标签、语义过滤——只要结论，不要解释。Not for judgments that must come with an explanation, analysis or a written reply; not for writing, summarizing or extracting text; not for math or date arithmetic. To design or code a TypeSafe integration inside an application, use the official `typesafe-ai` skill. Unofficial; calls TypeSafe's Jev model through the TypeSafe API (default) or OpenRouter.