transformers Agent Skills & AI Rules

GitHub

Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference...

168,002 stars Python Python 20 files ยท ~125,774 tokens #audio#deep-learning#deepseek#gemma#glm#hacktoberfest#llm#machine-learning
RAW Rules
6 Discovered Rules โ€ข ~3,258 Estimated Tokens
Quick:
Loading skill content...

AI Agent Protocol & Instructions

AGENTS.md root-instruction ~792 tokens
Raw
## Commands

- `make style` โ€” ruff format + lint (required for code style checks).
- `make typing` โ€” ty type checker and model structure rules.
- `make fix-repo` โ€” the `make style` fixes plus copies, modular conversions, doc TOCs, docstrings.
- `make check-repo` โ€” `make typing` plus consistency checks.
- `RUN_SLOW=1 pytest ...` โ€” many tests are marked slow and skipped in CI.

Run `make style` (or `make fix-repo`) as the last step before opening a PR.

## Local agent setup

Hosted review agents read this file via the root `AGENTS.md` / `CLAUDE.md` symlinks. Local agents wire their own assets: `make codex` (โ†’ `.agents/`), `make claude` (โ†’ `.claude/`).

## Before opening a PR

- Coordinate on the matching issue first. Do not open a PR for someone else's issue without explicit approval from its author or a maintainer in the thread; if approval is unclear, ask instead of drafting.
- Check for overlapping work, and do not open a second PR for a fix already covered:

  ```bash
  gh issue view <issue_number> --repo huggingface/transformers --comments
  gh pr list --repo huggingface/transformers --state open --search "<issue_number> in:body"
  gh pr list --repo huggingface/transformers --state open --search "<short area keywords>"
  ```

  If your approach is materially different, say why a second PR is needed in the issue.
- No one-off PRs for tiny edits (a single typo, an isolated lint fix). Mechanical cleanups are fine, but not as a first contribution.
- First-time contributors should not submit agent-written PRs or issues โ€” see `CONTRIBUTING.md` and the PR template. Code agents must warn users who are not already contributors, including the risk of being blocked.

## Copies and modular models

Model files in `src/transformers/models/` avoid inheriting from each other, so duplication is managed two ways โ€” modular is the current one, copies are legacy:

1. `# Copied from ...` marks a copied class or function. `make fix-repo` re-syncs it, so editing inside such a block is reverted โ€” edit the source it copies from, or deliberately break the link. **Do not add new `# Copied from` statements**; write a modular file instead.
2. A `modular_<name>.py` **may** inherit from other models; `make fix-repo` generates the standalone `modeling_*.py` and friends from it. Never edit a generated file when a modular one exists. Guide: [modular_transformers.md](../docs/source/en/modular_transformers.md).

Two modular traps:

- **Other models inherit your modular file.** `modular_deepseek_vl.py` also generates `modeling_deepseek_vl_hybrid.py`. Run `make fix-repo` and check everything it rewrote; hand-editing only the generated file you had in mind leaves the rest stale and `Check repository consistency` red.
- **`attr = AttributeError()` deletes an inherited attribute** โ€” it is an instruction to the converter, not a bug or placeholder. `raise AttributeError("...")` in a method body does the same for a method. Substituting a "real" value silently changes behaviour (`_no_split_modules = AttributeError()` โ†’ `[]` changes how the model may be sharded). See [Removing attributes](../docs/source/en/modular_transformers.md#removing-attributes) and [Deleting unused methods](../docs/source/en/modular_transformers.md#deleting-unused-methods).