FreePublished on GitHub

fengshenbang-lm

Operate the Fengshenbang-LM Fengshen package for pipelines, model families, data/training utilities, examples, and conversion planning.

The English summary is being prepared. Showing the original description.

VectorSpaceLab/AREX-Skill

Run score Not tested

See how to install

Files included (42)

SKILL.md3.8 KB
references/installation.md3.0 KB
references/repo-provenance.md1.8 KB
references/repo-routing-metadata.json548 B
references/troubleshooting.md3.6 KB
scripts/check_fengshen_install.py2.4 KB
sub-skills/data-training/references/data-formats.md7.2 KB
sub-skills/data-training/references/distributed-training.md5.1 KB
sub-skills/data-training/references/metrics-and-validation.md4.0 KB
sub-skills/data-training/references/pretraining-workflows.md6.1 KB
sub-skills/data-training/references/training-arguments.md7.5 KB
sub-skills/data-training/references/troubleshooting.md5.4 KB
sub-skills/data-training/scripts/check_ner_labels.py4.8 KB
sub-skills/data-training/scripts/inspect_training_args.py7.0 KB
sub-skills/data-training/SKILL.md2.7 KB
sub-skills/examples-conversion/references/clue-and-task-recipes.md6.8 KB
sub-skills/examples-conversion/references/conversion-utilities.md8.6 KB
sub-skills/examples-conversion/references/model-family-recipes.md7.7 KB
sub-skills/examples-conversion/references/nlg-nlt-recipes.md9.0 KB
sub-skills/examples-conversion/references/taiyi-diffusion.md7.9 KB
sub-skills/examples-conversion/references/troubleshooting.md8.7 KB
sub-skills/examples-conversion/references/ziya-llama.md9.3 KB
sub-skills/examples-conversion/scripts/check_recipe_requirements.py3.7 KB
sub-skills/examples-conversion/scripts/plan_ziya_conversion.py3.0 KB
sub-skills/examples-conversion/SKILL.md5.7 KB
sub-skills/model-zoo/references/api-reference.md10.0 KB
sub-skills/model-zoo/references/auto-and-tokenizers.md9.0 KB
sub-skills/model-zoo/references/compatibility.md7.4 KB
sub-skills/model-zoo/references/model-overview.md9.5 KB
sub-skills/model-zoo/references/troubleshooting.md10.4 KB
sub-skills/model-zoo/scripts/check_model_imports.py11.0 KB
sub-skills/model-zoo/SKILL.md3.5 KB
sub-skills/pipelines-cli/references/cli-reference.md5.4 KB
sub-skills/pipelines-cli/references/sequence-tagging.md4.5 KB
sub-skills/pipelines-cli/references/tcbert.md3.6 KB
sub-skills/pipelines-cli/references/text-classification.md5.2 KB
sub-skills/pipelines-cli/references/troubleshooting.md6.0 KB
sub-skills/pipelines-cli/references/unimc-uniex-ubert.md5.5 KB
sub-skills/pipelines-cli/scripts/inspect_pipeline_cli.py8.9 KB
sub-skills/pipelines-cli/scripts/make_classification_fixture.py5.5 KB
sub-skills/pipelines-cli/scripts/make_sequence_tagging_fixture.py4.6 KB
sub-skills/pipelines-cli/SKILL.md3.2 KB

SKILL.md (original)

Review the instructions the agent will receive before you install.

Fengshenbang-LM repo skill

Use this skill when the task involves the Fengshenbang-LM / fengshen Python package: Chinese NLP model families, fengshen-pipeline, Fengshen pipeline APIs, dataloaders, PyTorch Lightning training helpers, Deepspeed/Megatron planning, model-family examples, Taiyi/Ziya recipes, or checkpoint conversion planning.

First checks

Read references/installation.md before installing or repairing the package. This repo is sensitive to the age of the Transformers, Lightning, Torchmetrics, NumPy, and Setuptools stack.
Run the safe install check when an environment is available:
```
python scripts/check_fengshen_install.py --check-cli-help
```
This imports package modules and inspects CLI help only; it does not download models or launch training.
If imports, CLI help, optional CUDA, model downloads, submodules, or hard-coded example paths fail, read references/troubleshooting.md.
Use references/repo-provenance.md to decide whether this skill matches the current package checkout or should be refreshed.

Route by task

User task	Read
Use `fengshen-pipeline`, inspect pipeline CLI flags, create tiny classification/NER fixtures, adapt text classification or sequence-tagging data, use UniMC/UniEX/Ubert/TCBert APIs	sub-skills/pipelines-cli/SKILL.md
Choose or import Fengshen model/config/tokenizer families, understand top-level exports, custom auto/config keys, model compatibility, or model import failures	sub-skills/model-zoo/SKILL.md
Prepare/validate data, inspect `UniversalDataModule`, metrics, checkpoints, optimizer/scheduler/Trainer flags, pretraining data, Deepspeed/Megatron/fused-kernel planning	sub-skills/data-training/SKILL.md
Plan CLUE/classification recipes, NLG/NLT examples, Taiyi Stable Diffusion, Ziya inference/fine-tuning/conversion, delta/TF/diffusers/LLaMA conversion utilities	sub-skills/examples-conversion/SKILL.md

Package facts to remember

Distribution/import package: fengshen.
Version in package metadata: 0.0.1.
Console entry point: fengshen-pipeline = fengshen.cli.fengshen_pipeline:main.
CLI pattern: fengshen-pipeline <pipeline_module_name> predict|train ...; source CLI supports only predict and train methods.
Public top-level exports include Longformer, RoFormer, Megatron-T5, and Ubert classes/pipelines.
Many examples are real but heavy: they may require model/data downloads, CUDA/Deepspeed, multi-GPU launchers, large memory, checkpoint mutation, or maintainer-local paths. Treat them as planning evidence unless the user explicitly authorizes backend verification and execution.

Non-goals and safety

Do not run original repo examples, pretraining scripts, stable-diffusion scripts, Ziya conversion scripts, or fused-kernel tests by default.
Do not tell the user to open files in the original repository checkout as runtime instructions. Use this skill's bundled references and scripts.
Do not claim CUDA/Deepspeed/large-model execution is verified from CPU import checks.
Ask before network downloads, large model/dataset cache use, GPU allocation, multi-node jobs, checkpoint conversion, or overwriting output directories.
If a task is about editing or refreshing this generated skill after the source repo changes, use the repo-skill refresh workflow rather than relying on stale guidance.

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Install

Install with a command

npx skills add https://github.com/VectorSpaceLab/AREX-Skill --skill fengshenbang-lm

Paste it into your terminal and run it (requires Node.js). You can choose which agents to install it for, such as Claude Code or Codex.

Ask your agent

Please install the following Agent Skill.
https://github.com/VectorSpaceLab/AREX-Skill/tree/main/skills/repositories/repo-skills/fengshenbang-lm

First review SKILL.md and the bundled files and confirm there is nothing suspicious (such as sending data externally or reading credentials). Then place it in ~/.claude/skills/fengshenbang-lm/ for Claude Code, or ~/.agents/skills/fengshenbang-lm/ for Codex.

Send this text to Claude Code or Codex as is. It checks the contents before installing.

View source on GitHub

Repository: VectorSpaceLab/AREX-Skill
Stars: 341
Forks: 26
Category: Data & AI
License: Apache-2.0
Original language: English
Last updated: Sep 3, 2026

A skill is a set of instructions and scripts for an agent. cccskills does not guarantee that skills are safe. Review the contents before you install.