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Hugging Face Community Evals

hugging-face-community-evals

sickn33/agentic-awesome-skills

Run evaluations for Hugging Face Hub models using inspect-ai and lighteval on local hardware. Handles backend selection, local GPU evals, and choosing between vLLM, Transformers, and accelerate.

Hugging Face Model Card Evaluation

hugging-face-evaluation

sickn33/agentic-awesome-skills

This skill enables users to add and manage structured evaluation results within Hugging Face model cards. It supports extracting evaluation tables from README files, importing benchmark scores via the Artificial Analysis API, and executing custom model evaluations using vLLM or lighteval backends. It ensures compatibility with the model-index metadata format for standardized model releases.

Hugging Face Model Trainer

hugging-face-model-trainer

sickn33/agentic-awesome-skills

Train or fine-tune language and vision models using TRL or Unsloth on Hugging Face Jobs infrastructure. Supports SFT, DPO, GRPO methods and GGUF conversion for local deployment. Requires Pro account and HF_TOKEN for Hub saving. Optimized for cloud GPU training without local setup.

Hugging Face Paper Publisher

hugging-face-paper-publisher

sickn33/agentic-awesome-skills

Publish and manage research papers on Hugging Face Hub. Supports creating paper pages, linking papers to models/datasets, claiming authorship, and generating professional markdown-based research articles. Ideal for AI engineers and researchers.

Hugging Face Papers Lookup

hugging-face-papers

sickn33/agentic-awesome-skills

Look up Hugging Face paper pages as markdown and query the papers API for structured metadata including authors, linked models, datasets, Spaces, GitHub repos, and project pages. Ideal for summarizing or analyzing AI research papers from hf.co or arXiv URLs and IDs.

Hugging Face Vision Model Trainer

hugging-face-vision-trainer

sickn33/agentic-awesome-skills

Train object detection, image classification, and SAM/SAM2 segmentation models locally or on Hugging Face Jobs with dataset validation and Hub saving.

HuggingFace Best Model Finder

huggingface-best

sickn33/agentic-awesome-skills

This skill helps users find the best AI models for specific tasks by querying Hugging Face benchmark leaderboards. It analyzes hardware constraints like GPU VRAM or CPU memory to filter compatible models. The output includes a comparison table with benchmark scores, parameter sizes, licenses, and device compatibility status. It also suggests whether models can run locally or require API access.

Hugging Face Local Model Evaluation

huggingface-community-evals

sickn33/agentic-awesome-skills

This skill guides users on running evaluations against models on the Hugging Face Hub using local hardware. It covers using inspect-ai and lighteval frameworks with local inference backends like vllm, Transformers, or accelerate. It includes task selection, smoke testing, and hardware guidance for different model sizes. It does not cover remote orchestration or publishing results to the community workflow.

Hugging Face Local Models

huggingface-local-models

sickn33/agentic-awesome-skills

This skill helps you select and run large language models locally using llama.cpp and GGUF formats. It covers finding compatible models on the Hugging Face Hub, choosing quantization levels for different hardware like CPU, Mac Metal, CUDA, or ROCm, and launching servers via llama-cli or llama-server. It also includes instructions for converting weights and verifying OpenAI-compatible local serving endpoints.

Hugging Face Spaces Deployment

huggingface-spaces

sickn33/agentic-awesome-skills

Build, deploy, and maintain machine-learning applications on Hugging Face Spaces using Gradio, Docker, or Static SDKs, with ZeroGPU and dedicated hardware, model loading, debugging, and inference providers.

Hugging Face API Tool Builder

huggingface-tool-builder

sickn33/agentic-awesome-skills

This skill enables users to build reusable command-line scripts and utilities for interacting with the Hugging Face API. It supports chaining API calls, automating repetitive tasks, and processing model or dataset data efficiently. Scripts utilize HF_TOKEN for authentication and can leverage the hf CLI for advanced repository interactions.

LLM AI Feature Bug Hunting

sickn33/agentic-awesome-skills

This skill focuses on identifying security vulnerabilities in Large Language Model (LLM) and AI features. It covers prompt injection, system prompt leakage, cross-tenant access, and data exfiltration techniques. Users must verify findings against false positives using reproducibility checks and out-of-band callbacks before reporting.

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