pipelines
Pipelines provide the simplest way to use pre-trained models for inference. They abstract away tokenization, model loading, and post-processing, offering a unified interface for dozens of tasks.
- Skills
- Scientific
- 1
What it does and how to use it
A skill that teaches Claude Code to do scientific tasks well. It is packaged knowledge the model uses whenever it is relevant.
- Install the skill (command above).
- In Claude Code, describe what you need - the skill turns on by itself when the context fits.
- No commands to memorize: you talk in plain language and the skill does the rest.
Install (Claude Code)
mkdir -p .claude/skills/pipelines && curl -fsSL https://doutorai.pt/data/lib/skills__pipelines.md -o .claude/skills/pipelines/SKILL.mdPaste this command into the terminal, in your project folder, and the component installs automatically.
Content
# Pipeline API Reference
## Overview
Pipelines provide the simplest way to use pre-trained models for inference. They abstract away tokenization, model loading, and post-processing, offering a unified interface for dozens of tasks.
## Basic Usage
Create a pipeline by specifying a task:
```python
from transformers import pipeline
# Auto-select default model for task
pipe = pipeline("text-classification")
result = pipe("This is great!")
```
Or specify a model:
```python
pipe = pipeline("text-classification", model="distilbert-base-uncased-finetuned-sst-2-english")
```
## Supported Tasks
- 🔒 Full content on the Pro plan (€7.99/month) -Need help with Claude Code?
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