playbooks: pull-hf-model — generic HF→ana-ml2 cache puller
Codifies the previously-manual workflow described in
stacks/llama-swap/README.md: install hf CLI via pipx (one-time),
inject hf_transfer for fast multi-connection downloads,
`hf download` into the shared HF cache at /tank/aimodels/huggingface
with optional --include filter.
Model-format-agnostic by design — same playbook handles GGUFs for
llama-swap and safetensors for vLLM (both stacks read the same cache
dir via HF_HOME=/hfcache). Does NOT edit any consumer's config.yaml;
per-model run params (ctx-size, sampler defaults, quant choice,
chat template, etc.) stay human-curated.
Usage:
scripts/elway ana-ml2 --playbook playbooks/pull-hf-model.yaml \
--var hf_repo=<user>/<repo> \
[--var allow_patterns='*Q6_K*']
Idempotent: hf CLI skips already-cached blobs; re-runs are
sub-second when the snapshot is already complete.
Smoke-tested 2026-05-13 against:
- mradermacher/Selene-1-Mini-Llama-3.1-8B-GGUF (Q6_K, ~6.5 GB)
- Skywork/Skywork-Reward-V2-Llama-3.1-8B (full safetensors, ~16 GB)
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# Pull a model from HuggingFace into ana-ml2's shared HF cache
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# (`/tank/aimodels/huggingface/`). Model-format-agnostic — handles GGUFs,
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# safetensors, or anything else HF hosts.
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#
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# Consumers (llama-swap, vLLM, others) read from the same cache:
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# - llama-swap's config.yaml references entries via `-hf <user>/<repo>`
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# - vLLM stacks reference via `--model <user>/<repo>` with HF_HOME mounted
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#
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# This playbook does NOT edit any consumer config. Run it for the download,
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# then hand-edit the relevant `stacks/<consumer>/conf/*.yaml` and deploy
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# that consumer separately. Keeps the download mechanical and the
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# per-model params (ctx-size, quant choice, sampler defaults, etc.) where
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# they belong — in human-curated config.
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#
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# Usage:
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#
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# # Full repo (e.g. safetensors for later AWQ quant + vLLM serving):
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# scripts/elway ana-ml2 --playbook playbooks/pull-hf-model.yaml \
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# --var hf_repo=Skywork/Skywork-Reward-V2-Llama-3.1-8B
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#
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# # Single quant pattern (e.g. one GGUF for llama-swap):
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# scripts/elway ana-ml2 --playbook playbooks/pull-hf-model.yaml \
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# --var hf_repo=mradermacher/Selene-1-Mini-Llama-3.1-8B-GGUF \
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# --var allow_patterns='*Q6_K*'
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#
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# allow_patterns is forwarded to `hf download --include` — set it to filter
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# down to specific files (e.g. `*UD-Q6_K_XL*` or `*Q6_K*.gguf`). Omit to
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# pull every file in the repo.
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vars:
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hf_repo: "" # REQUIRED, e.g. unsloth/Qwen3.6-35B-A3B-GGUF
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allow_patterns: "" # OPTIONAL, e.g. "*Q6_K*"
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hf_cache_dir: /tank/aimodels/huggingface
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steps:
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# ── Sanity: refuse to run with an empty hf_repo. ──────────────────────
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- name: Check hf_repo is set
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shell: |
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[ -n "{{ hf_repo }}" ] || {
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echo "elway: --var hf_repo=<user>/<repo> is required" >&2
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exit 2
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}
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changed_when: "false"
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# ── Tooling: install `hf` CLI via pipx once, inject hf_transfer for
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# the fast multi-connection download path. Both no-ops if
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# already installed. ──────────────────────────────────────
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- name: Install huggingface_hub via pipx (one-time)
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shell: pipx install --quiet huggingface_hub
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creates: ~/.local/bin/hf
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- name: Inject hf_transfer for faster downloads
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# pipx inject is idempotent — if hf_transfer is already in the
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# huggingface_hub venv, this is a fast no-op. Cheaper to run
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# unconditionally than to glob-check the venv path (elway's
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# creates: doesn't expand shell globs).
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shell: pipx inject --quiet huggingface_hub hf_transfer
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changed_when: "false"
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# ── Pull. hf CLI is itself idempotent — re-runs only fetch missing
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# blobs, so safe to invoke unconditionally. ─────────────────
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- name: Pull {{ hf_repo }} into {{ hf_cache_dir }}
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shell: |
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export PATH="$HOME/.local/bin:$PATH"
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pat="{{ allow_patterns }}"
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args=""
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if [ -n "$pat" ]; then
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args="--include $pat"
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fi
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HF_HOME={{ hf_cache_dir }} \
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HF_HUB_ENABLE_HF_TRANSFER=1 \
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hf download {{ hf_repo }} $args
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# changed_when:false — hf CLI doesn't expose pulled-vs-cached cheaply,
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# and a `du` diff would itself take seconds on a multi-GB repo. Accept
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# always-reporting-ok here; the verify step below confirms presence.
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changed_when: "false"
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- name: Verify cache hit for {{ hf_repo }}
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shell: |
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# hf normalizes user/repo to models--user--repo in the hub cache.
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slug=$(printf '%s' "{{ hf_repo }}" | tr '/' '~')
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slug=${slug//\~/--}
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d="{{ hf_cache_dir }}/hub/models--${slug}"
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[ -d "$d" ] || { echo "elway: cache dir not found for {{ hf_repo }} at $d" >&2; exit 1; }
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n=$(find "$d/snapshots/" -mindepth 2 -maxdepth 2 \( -type f -o -type l \) 2>/dev/null | wc -l)
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[ "$n" -gt 0 ] || { echo "elway: snapshot dir exists but is empty under $d" >&2; exit 1; }
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echo "elway: $n files present under $d/snapshots/"
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changed_when: "false"
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verify:
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- name: hf CLI installed
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shell: test -x ~/.local/bin/hf
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changed_when: "false"
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- name: HF cache dir writable by SSH user
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shell: test -w {{ hf_cache_dir }}
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changed_when: "false"
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- name: Model present in cache (post-pull)
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shell: |
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slug=$(printf '%s' "{{ hf_repo }}" | tr '/' '~')
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slug=${slug//\~/--}
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d="{{ hf_cache_dir }}/hub/models--${slug}"
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test -d "$d" && [ -n "$(find $d/snapshots/ -mindepth 2 -maxdepth 2 \( -type f -o -type l \) 2>/dev/null | head -1)" ]
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changed_when: "false"
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