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hf-layer-package-jobs

Apps & Automation
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Use when changing mesh-llm automation or CLI flows that discover Hugging Face GGUF models, plan CPU Hugging Face Jobs for layer-package splitting, estimate max cost, or publish skippy layer packages/catalog entries.

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HF Layer Package Jobs

Use this skill for the models package CLI, the model-package crate, and the daily Unsloth queue workflow. This skill starts after a quantized GGUF artifact exists. It does not quantize models; use hf-gguf-quant-jobs first or hf-quant-and-layer-package-jobs when quantization and layer packaging should run in one job.

Workflow

  1. Keep model refs in colon-selector form such as unsloth/Qwen3-8B-GGUF:Q4_K_M; do not split the quant into a separate --quant argument for generated job inputs.
  2. Treat package submission as spend-bearing. The default behavior must be a dry run that prints the resolved package plan, effective timeout, selected HF Jobs hardware, and maximum cost. Require --confirm before submitting jobs.
  3. Splitting is CPU and I/O bound. The HF Jobs hardware does not need enough RAM or VRAM to hold the full model; use CPU hardware suitable for running the splitter/build and scale timeout/cost estimates with model file size.
  4. If the bucket script is stale during a confirmed submission, update it automatically before queuing jobs. Dry runs should avoid side effects.
  5. The GitHub workflow should default to dry run. When confirmed, it should pass --confirm, submit at most the requested number of jobs, wait for every submitted HF Job, and fail if any job finishes unsuccessfully.
  6. Prefer family-diverse candidate ordering after ranking by selected quant size, so one run does not consume the whole queue on a single model family.

Commands

Preview a package job:

mesh-llm models package <gguf-repo>:<quant-selector> --dry-run

Submit and follow:

mesh-llm models package <gguf-repo>:<quant-selector> --confirm --follow

Inspect jobs:

mesh-llm models package --status <job-id>
mesh-llm models package --logs <job-id>
mesh-llm models package --list

For local package certification after the artifact exists:

mesh-llm models certify <layer-package-ref> --package-only --json

Local Package Workflow

When the quantized GGUF is already available on the local machine, build the package locally with skippy-model-package, then publish the package directory to a Hugging Face model repo:

just build

target/debug/skippy-model-package write-package \
  <org>/<gguf-repo>:<quant-selector> \
  --out-dir /tmp/<model>-layers

target/debug/skippy-model-package preflight \
  /tmp/<model>-layers \
  --verify-sha256

hf repo create <org>/<layer-package-repo> --type model --private
hf upload <org>/<layer-package-repo> /tmp/<model>-layers . --repo-type model

For local GGUF paths outside the Hugging Face cache, include explicit provenance flags on write-package: --model-id, --source-repo, --source-revision, and --source-file.

Validation

Run Rust formatting and the focused package checks before committing:

cargo fmt --all -- --check
cargo test -p model-package
cargo check -p mesh-llm-host-runtime

For behavior smoke tests, use a tiny dry run first:

cargo run -p model-package --bin queue-unsloth-layer-packages -- --max-jobs 1 --recent-limit 3 --popular-limit 3 --dry-run