nlp-pipeline-builder
Natural language processing ML pipelines for text classification, NER, sentiment analysis, text generation, and embeddings. Activates for "nlp", "text classification", "sentiment analysis", "named entity recognition", "BERT", "transformers", "text preprocessing", "tokenization", "word embeddings". Builds NLP pipelines with transformers, integrated with SpecWeave increments.
npx skills add majiayu000/claude-skill-registry --skill nlp-pipeline-builder-anton-abyzov-specweave --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# NLP Pipeline Builder ## Overview Specialized ML pipelines for natural language processing. Handles text preprocessing, tokenization, transformer models (BERT, RoBERTa, GPT), fine-tuning, and deployment for production NLP systems. ## NLP Tasks Supported ### 1. Text Classification ```python from specweave import NLPPipeline # Binary or multi-class text classification pipeline = NLPPipeline( task="classification", classes=["positive", "negative", "neutral"], increment="0042" ) # Automatically configures: # - Text preprocessing (lowercase, clean) # - Tokenization (BERT tokenizer) # - Model (BERT, RoBERTa, DistilBERT) # - Fine-tuning on your data # - Inference pipeline pipeline.fit(train_texts, train_labels) ``` ### 2. Named Entity Recognition (NER) ```python # Extract entities from text pipeline = NLPPipeline( task="ner", entities=["PERSON", "ORG", "LOC", "DATE"], increment="0042" ) # Returns: [(entity_text, entity_type, start_pos, end_pos), ...] ``` ### 3. Sentiment Analysis ```python # Sentiment classification (specialized) pipeline = NLPPipeline( task="sentiment", increment="0042" ) # Fine-tuned for sentiment (positive/negative/neutral) ``` ### 4. Text Generation ```python # Gener
- Overview
- NLP Tasks Supported
- 1. Text Classification
- 2. Named Entity Recognition (NER)
- 3. Sentiment Analysis
- 4. Text Generation
- Best Practices for NLP
- Text Preprocessing
- Model Selection
- Transfer Learning
- Handling Long Text
- Integration with SpecWeave
- Commands
What does the nlp-pipeline-builder skill do?
Natural language processing ML pipelines for text classification, NER, sentiment analysis, text generation, and embeddings. Activates for "nlp", "text classification", "sentiment analysis", "named entity recognition", "BERT", "transformers", "text preprocessing", "tokenization", "word embeddings". Builds NLP pipelines with transformers, integrated with SpecWeave increments.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill nlp-pipeline-builder-anton-abyzov-specweave --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.