본문으로 건너뛰기
cccskills
무료GitHub에 공개

tinker-cli

Guide for the Tinker CLI — managing training runs, checkpoints, downloading weights, and publishing to HuggingFace. Use when the user asks about CLI commands, listing runs, managing checkpoints from the terminal, or uploading to HF Hub.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

연동 도구Hugging Face
설치 방법 보기

포함된 파일(1)

  • SKILL.md3.7 KB

SKILL.md(원문)

설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.

Tinker CLI

The tinker CLI is installed with the Tinker Python SDK. It provides commands for managing training runs and checkpoints from the terminal.

Requires TINKER_API_KEY environment variable to be set.

Global options

tinker --format table   # Rich table output (default)
tinker --format json    # JSON output (for scripting)

Training runs

# List recent training runs
tinker run list
tinker run list --limit 50

# Show details for a specific run
tinker run info <RUN_ID>

# Custom columns
tinker run list --columns id,model,lora,updated,status,checkpoint

Available columns: id, model, owner, lora, updated, status, checkpoint, checkpoint_time.

Checkpoints

List and inspect

# List checkpoints for a specific run
tinker checkpoint list --run-id <RUN_ID>

# List all your checkpoints across runs
tinker checkpoint list
tinker checkpoint list --limit 50

# Show checkpoint details
tinker checkpoint info <TINKER_PATH>

Download

# Download and extract a checkpoint
tinker checkpoint download <TINKER_PATH>
tinker checkpoint download <TINKER_PATH> --output ./my-adapter
tinker checkpoint download <TINKER_PATH> --force  # Overwrite existing

Visibility

# Make a checkpoint publicly accessible
tinker checkpoint publish <TINKER_PATH>

# Make a checkpoint private
tinker checkpoint unpublish <TINKER_PATH>

TTL (expiration)

# Set checkpoint to expire in 24 hours
tinker checkpoint set-ttl <TINKER_PATH> --ttl 86400

# Remove expiration (keep indefinitely)
tinker checkpoint set-ttl <TINKER_PATH> --remove

Delete

# Delete checkpoints (with confirmation prompt)
tinker checkpoint delete <TINKER_PATH>

# Delete without confirmation
tinker checkpoint delete <TINKER_PATH> -y

# Delete multiple
tinker checkpoint delete <PATH1> <PATH2> <PATH3>

Upload to HuggingFace Hub

# Push checkpoint to HuggingFace
tinker checkpoint push-hf <TINKER_PATH> --repo user/my-model

# Push as public repo
tinker checkpoint push-hf <TINKER_PATH> --repo user/my-model --public

# Advanced options
tinker checkpoint push-hf <TINKER_PATH> \
    --repo user/my-model \
    --revision main \
    --commit-message "Upload fine-tuned model" \
    --create-pr \
    --no-model-card

Options: --repo, --public, --revision, --commit-message, --create-pr, --allow-pattern, --ignore-pattern, --no-model-card.

Version

tinker version   # e.g. "tinker 0.15.0"

Common patterns

Script-friendly output

# Get checkpoint paths as JSON for scripting
tinker checkpoint list --format json | jq '.[].tinker_path'

# Get run IDs
tinker run list --format json | jq '.[].id'

Typical workflow

# 1. Find your training run
tinker run list

# 2. List checkpoints for that run
tinker checkpoint list --run-id <RUN_ID>

# 3. Download the final checkpoint
tinker checkpoint download tinker://<RUN_ID>/sampler_weights/final -o ./adapter

# 4. Or push directly to HuggingFace
tinker checkpoint push-hf tinker://<RUN_ID>/sampler_weights/final --repo user/my-model

Common pitfalls

  • TINKER_API_KEY must be set — the CLI reads it from the environment
  • Checkpoint paths use the format tinker://<run-id>/<type>/<checkpoint-id>
  • push-hf uploads the raw checkpoint — for merged HF models, use weights.build_hf_model() in Python first (see /weights skill)
  • delete is permanent and irreversible — use -y flag carefully

리뷰

아직 리뷰가 없습니다. 사용해 본 소감을 남겨 주세요.

댓글

로그인 없이 쓸 수 있습니다. 사용 후기, 질문, 작동하지 않은 환경 등을 편하게 남겨 주세요.

아직 댓글이 없습니다. 첫 댓글을 남겨 보세요.

보내면 바로 공개됩니다. 이메일 주소나 전화번호 같은 개인 정보는 쓰지 마세요. URL은 2개까지입니다.

0 / 1,000자

이 양식은 reCAPTCHA로 보호되며 Google 개인정보처리방침 및 서비스 약관이 적용됩니다.

같은 저장소의 스킬

Guide for checkpointing — saving, loading, and resuming training with CheckpointRecord. Use when the user asks about saving weights, resuming training, checkpoint management, or the checkpoint lifecycle.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

uiuc-kang-lab/rlvr_generalization_bounds52026년 5월 13일 업데이트

ci

무료

Guide for testing conventions and CI pipelines — unit tests, integration smoke tests, pytest markers, and GitHub Actions workflows. Use when the user asks about testing, CI, running tests, or adding tests for a recipe.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

uiuc-kang-lab/rlvr_generalization_bounds52026년 5월 13일 업데이트

Guide for using completers — TokenCompleter and MessageCompleter for text generation during RL rollouts and evaluation. Use when the user asks about generating text, completing messages, or using completers in RL environments.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

uiuc-kang-lab/rlvr_generalization_bounds52026년 5월 13일 업데이트

Guide for contributing to the tinker-cookbook repo — development setup, code style, type checking, PR process, and design conventions. Use when the user asks about how to contribute, set up the dev environment, code style, or project conventions.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

uiuc-kang-lab/rlvr_generalization_bounds52026년 5월 13일 업데이트

datasets

무료

Guide for dataset construction — SupervisedDatasetBuilder, RLDatasetBuilder, ChatDatasetBuilder, and custom dataset creation from JSONL, HuggingFace, or conversation data. Use when the user asks about datasets, data loading, data preparation, or custom data formats.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

uiuc-kang-lab/rlvr_generalization_bounds52026년 5월 13일 업데이트

Set up and run knowledge distillation (on-policy, off-policy, or multi-teacher) from a teacher model to a student model using the Tinker API. Use when the user wants to distill knowledge, compress models, or train a student from a teacher.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

uiuc-kang-lab/rlvr_generalization_bounds52026년 5월 13일 업데이트

uiuc-kang-lab의 스킬 모두 보기

이 스킬의 문제 신고