AI & machine learning · Skill set · 10 skills
Hugging Face Hub and models
Find the best model for a task, estimate memory, run models locally or in the browser with Transformers.js, use datasets and papers, post-train with TRL, track runs and plan a SageMaker deploy.
Open in PhởSkills in this set
- HuggingFace Best Model Finder
Use when the user asks about finding the best, top, or recommended model for a task, wants to know what AI model to use, or wants to compare models by benchmark scores. Triggers…
- Hf mem
Hugging Face CLI to estimate the required memory to load Safetensors or GGUF model weights for inference from the Hugging Face Hub
- Hugging Face Local Models
Use to select models to run locally with llama.cpp and GGUF on CPU, Mac Metal, CUDA, or ROCm. Covers finding GGUFs, quant selection, running servers, exact GGUF file lookup…
- Transformers.js - Machine Learning for JavaScript
Use Transformers.js to run state-of-the-art machine learning models directly in JavaScript/TypeScript. Supports NLP (text classification, translation, summarization), computer…
- Hugging Face Dataset Viewer
Use this skill for Hugging Face Dataset Viewer API workflows that fetch subset/split metadata, paginate rows, search text, apply filters, download parquet URLs, and read size or…
- Hugging Face Paper Pages
Look up and read Hugging Face paper pages in markdown, and use the papers API for structured metadata such as authors, linked models/datasets/spaces, Github repo and project…
- Hf cli
Hugging Face Hub CLI (`hf`) for downloading, uploading, and managing models, datasets, spaces, buckets, repos, papers, jobs, and more on the Hugging Face Hub. Use when: handling…
- TRL
Post-train LLMs with TRL (Transformers Reinforcement Learning) — SFT, DPO, GRPO, KTO, and reward-model training. Use when writing or debugging training code with the TRL Python…
- Trackio - Experiment Tracking for ML Training
Track and visualize ML training experiments with Trackio. Use when logging metrics during training (Python API), firing alerts for training diagnostics, or retrieving/analyzing…
- SageMaker Deployment Planner
Plan and coordinate the deployment of a model to Amazon SageMaker AI. Use this skill whenever the user wants to deploy, host, serve, or expose a model on SageMaker or AWS —…
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Frequently asked questions
What is in the Hugging Face Hub and models skill set?
10 skills: HuggingFace Best Model Finder, Hf mem, Hugging Face Local Models, Transformers.js - Machine Learning for JavaScript, Hugging Face Dataset Viewer, Hugging Face Paper Pages, and 4 more.
Is the Hugging Face Hub and models skill set free?
Yes. It is published by Hugging Face under the Apache 2.0 licence and works with a free Phở account.
How do I add Hugging Face Hub and models to Phở?
Press Open in Phở and add the set once. From then on Phở picks the right skill from it whenever a request matches.
Copied unchanged from huggingface/skills at commit 25910b3 and credited to Hugging Face, who is not affiliated with Phở. The full instructions and licence text ship with the skill inside Phở.