transformers
Hugging Face Transformers for loading Hub models, running pipeline inference, text generation, and Trainer fine-tuning on NLP, vision, audio, and multimodal tasks. Use when working with AutoModel, pipelines, tokenizers, or TrainingArguments—not for general ML outside the Transformers library.
npx skills add K-Dense-AI/scientific-agent-skills --skill transformers --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.
# Transformers ## Overview The Hugging Face Transformers library provides access to thousands of pre-trained models for tasks across NLP, computer vision, audio, and multimodal domains. Use this skill to load models, perform inference, and fine-tune on custom data. ## Installation Tested against **transformers 5.12.0** (current PyPI release; June 2026). Requires **Python 3.10+**; the `torch` extra currently requires **PyTorch 2.4+**. ```bash uv pip install "transformers[torch]==5.12.0" huggingface_hub==1.19.0 datasets==5.0.0 evaluate==0.4.6 accelerate==1.14.0 ``` For vision tasks, add: ```bash uv pip install timm==1.0.27 pillow==12.2.0 ``` For audio tasks, add: ```bash uv pip install librosa==0.11.0 soundfile==0.14.0 ``` These pins are for reproducible examples. For exploratory work, loosen them only after checking the Transformers and Hub release notes for API changes. Check your version: ```python import transformers print(transformers.__version__) ``` ## Authentication Many models on the Hugging Face Hub are gated or private. Authenticate before loading them. **Recommended:** CLI login (stores token in `~/.cache/huggingface/token`): ```bash hf auth login ``` **Python:** ```pytho
- Overview
- Installation
- Authentication
- Transformers v5
- Quick Start
- Core Capabilities
- 1. Pipelines for Quick Inference
- 2. Model Loading and Management
- 3. Text Generation
- 4. Training and Fine-Tuning
- 5. Tokenization
- Common Patterns
- Pattern 1: Simple Inference
- Pattern 2: Custom Model Usage
uv pip install "transformers[torch]==5.12.0" huggingface_hub==1.19.0 datasets==5.0.0 evaluate==0.4.6 accelerate==1.14.0 uv pip install timm==1.0.27 pillow==12.2.0 uv pip install librosa==0.11.0 soundfile==0.14.0 hf auth login export HF_TOKEN="..." # Read token from a secret manager, not source code
What does the transformers skill do?
Hugging Face Transformers for loading Hub models, running pipeline inference, text generation, and Trainer fine-tuning on NLP, vision, audio, and multimodal tasks. Use when working with AutoModel, pipelines, tokenizers, or TrainingArguments—not for general ML outside the Transformers library.
How do I install it?
Run `npx skills add K-Dense-AI/scientific-agent-skills --skill transformers --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 K-Dense-AI/scientific-agent-skills, a repository with 32,619 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.