获取 Hugging Face 上的模型、数据集和 Space 的统计信息
npx skills add https://github.com/cafe3310/public-agent-skills --skill hugging-face-stat
Hugging Face 官方页面默认主要展示“过去 30 天的下载量”。此技能通过底层的 API 扩展参数,允许大语言模型获取任意公开模型或数据集的历史总下载量 (downloadsAllTime),以及获取 Space 的运行硬件、点赞数与状态,并能汇总查询组织下所有模型的数据。
此技能提供了一个可靠的 Bash 脚本(hf_stats.sh),自带错误处理、超时机制和数值美化。
本技能提供了一个现成的 Bash 脚本 hf_stats.sh。当你需要查询 Hugging Face 数据时,必须直接调用该脚本。
<path_to_skill>/hf_stats.sh
当你需要查询一个模型或数据集的详细下载数据时:
# 查询模型
<path_to_skill>/hf_stats.sh model <repo_id>
# 查询数据集
<path_to_skill>/hf_stats.sh dataset <repo_id>
返回数据包括:库 ID、作者、创建时间、最近30天下载、历史总下载量、点赞数。
当你需要了解一个 Space 的热度与运行环境时:
<path_to_skill>/hf_stats.sh space <repo_id>
返回数据包括:库 ID、运行状态、硬件规格(如 T4 medium)、SDK 类型(如 Gradio)、点赞数。
当你需要汇总查询一个组织下所有模型的统计数据时:
<path_to_skill>/hf_stats.sh org <org_name>
返回数据包括:组织模型总数、最近30天总下载、总点赞数,并按下载量降序排列前20个热门模型。
repo_id 和类型(model, dataset, space, org)。Bash 工具运行本技能目录下的 hf_stats.sh 脚本。Create new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, edit, or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.
Access NCBI GEO for gene expression/genomics data. Search/download microarray and RNA-seq datasets (GSE, GSM, GPL), retrieve SOFT/Matrix files, for transcriptomics and expression analysis.
Bayesian modeling with PyMC. Build hierarchical models, MCMC (NUTS), variational inference, LOO/WAIC comparison, posterior checks, for probabilistic programming and inference.
Multi-objective optimization framework. NSGA-II, NSGA-III, MOEA/D, Pareto fronts, constraint handling, benchmarks (ZDT, DTLZ), for engineering design and optimization problems.
Statistical modeling toolkit. OLS, GLM, logistic, ARIMA, time series, hypothesis tests, diagnostics, AIC/BIC, for rigorous statistical inference and econometric analysis.
Add unsigned integer (uint) type support to PyTorch operators by updating AT_DISPATCH macros. Use when adding support for uint16, uint32, uint64 types to operators, kernels, or when user mentions enabling unsigned types, barebones unsigned types, or uint support.
Convert PyTorch AT_DISPATCH macros to AT_DISPATCH_V2 format in ATen C++ code. Use when porting AT_DISPATCH_ALL_TYPES_AND*, AT_DISPATCH_FLOATING_TYPES*, or other dispatch macros to the new v2 API. For ATen kernel files, CUDA kernels, and native operator implementations.
Write docstrings for PyTorch functions and methods following PyTorch conventions. Use when writing or updating docstrings in PyTorch code.
Take cafe3310/hugging-face-stat from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.