ProfessorGPTProfessorGPT
Hugging Face
Hugging FaceHugging Face· v1.0.0
codingOfficial
Official Provider SkillView repo

Set up slop-farmer for a GitHub repository end-to-end. Use this whenever the user mentions slop-farmer setup, creating a repo config, choosing scrape limits, checking GitHub rate limits, cleaning PR template boilerplate, inspecting issue/PR title patterns with gh, installing or authenticating the Hugging Face hf CLI, publishing datasets, reproducing dashboards, or deploying the static dashboard to a Hugging Face Space. Be proactive even if the user only asks for one piece of the setup, because c

Files6 files
SKILL.md451 lines
Loading editor…

Install

Recommended

One command — your agent picks it up automatically.

Select an AI agent above to see the install command.

or

Manual Install

More steps

Download the archive and add the files to your project manually.

Skill details

Versionv1.0.0
AuthorHugging Face
Categorycoding
Skill IDhuggingface/swarm-sweeper/skills/farmer-setup
Files6 files

Related skills

Custom BlocksUse when the user has written (or wants to write) a `ModularPipelineBlocks` subclass in a local Python file and needs to package it into a Hub-uploadable directory. Covers the workflow from a single `block.py` file to a published custom-block repo that consumers can load via `ModularPipeline.from_pretrained(<repo>, trust_remote_code=True)`.Diffusers CliUse when the user wants to run a diffusers pipeline from a terminal (one-off generation, batch jobs, smoke-testing a new model), run on HF Sandbox hardware via `--remote`, introspect a pipeline's input schema before calling it, or attach a LoRA at inference time. Prefer this over writing ad-hoc Python scripts for generation tasks.Model IntegrationUse when adding a new model or pipeline to diffusers, setting up file structure for a new model, converting a pipeline to modular format, or converting weights for a new version of an already-supported model.Peft Method ChangesUse when modifying an existing PEFT method (its forward method, parameters/buffers, state_dict handling, or config defaults) to ensure that existing checkpoints keep working.Trl TrainingPost-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 API or the trl CLI.Hf Cloud Aws Context DiscoveryDiscover the user's local AWS context (active profile, region, account ID, caller identity) at the start of any AWS task. Use this skill before any other AWS work — deploying to SageMaker, creating resources, calling AWS APIs, or anything that touches an AWS account. Use it especially when the user has not specified a region or profile explicitly, when they say things like "use my AWS account", "deploy to AWS", "use my profile", or when about to make any AWS CLI or SDK call. Never guess the regi