transformers
Loading and using pretrained models with Hugging Face Transformers. Use when working with pretrained models from the Hub, running inference with Pipeline API, fine-tuning models with Trainer, or handling text, vision, audio, and multimodal tasks.
npx skills add majiayu000/claude-skill-registry --skill transformers-itsmostafa-llm-engineering-skil --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.
# Using Hugging Face Transformers Transformers is the model-definition framework for state-of-the-art machine learning across text, vision, audio, and multimodal domains. It provides unified APIs for loading pretrained models, running inference, and fine-tuning. ## Table of Contents - [Core Concepts](#core-concepts) - [Pipeline API](#pipeline-api) - [Model Loading](#model-loading) - [Inference Patterns](#inference-patterns) - [Fine-tuning with Trainer](#fine-tuning-with-trainer) - [Working with Modalities](#working-with-modalities) - [Memory and Performance](#memory-and-performance) - [Best Practices](#best-practices) ## Core Concepts ### The Three Core Classes Every model in Transformers has three core components: ```python from transformers import AutoConfig, AutoModel, AutoTokenizer # Configuration: hyperparameters and architecture settings config = AutoConfig.from_pretrained("bert-base-uncased") # Model: the neural network weights model = AutoModel.from_pretrained("bert-base-uncased") # Tokenizer/Processor: converts inputs to tensors tokenizer = AutoTokenizer.from_pretrained("bert-base-uncased") ``` ### The `from_pretrained` Pattern All loading uses `from_pretrained()` which ha
- Table of Contents
- Core Concepts
- The Three Core Classes
- The frompretrained Pattern
- Auto Classes
- Pipeline API
- Text Tasks
- Chat/Conversational
- Vision Tasks
- Audio Tasks
- Multimodal Tasks
- Model Loading
- Device Placement
- Loading from Local Path
What does the transformers skill do?
Loading and using pretrained models with Hugging Face Transformers. Use when working with pretrained models from the Hub, running inference with Pipeline API, fine-tuning models with Trainer, or handling text, vision, audio, and multimodal tasks.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill transformers-itsmostafa-llm-engineering-skil --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.