Resmi Sağlayıcı Skill'iView repo
Cut a new transformers-mlinter release. Bumps the version across all pinned locations, updates the CHANGELOG, runs local checks and a packaged smoke test, drives the tag-based GitHub Actions publish to PyPI, then opens the next development version on main. Use when asked to release, cut a version, or ship X.Y.Z.
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SKILL.md150 satır
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Kurulum
ÖnerilenTek komut — ajanınız otomatik olarak devreye alır.
Kurulum komutunu görmek için yukarıdan bir AI aracı seçin.
veya
Manuel Kurulum
Daha fazla adımDosyayı indirin ve ajanınızın sistem istemine yapıştırın.
Skill detayları
Versiyonv1.0.0
YazarHugging Face
Kategoricoding
Skill IDhuggingface/transformers-mlinter/.ai/skills/release
İlgili skill'ler
Add Mlinter RuleAdd a new TRF rule to the mlinter. Checks for duplicates, creates the rule module and TOML entry, runs against all models, and handles violations (fix or allowlist).Remove Mlinter RuleRetire a TRF rule from the mlinter. Marks the rule deprecated in rules.toml, deletes its module and tests, and records the removal in the CHANGELOG. Use when asked to remove, retire, drop, or delete a rule.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.