# Hugging Face Vision Trainer

> Train or fine-tune vision models on Hugging Face Jobs for detection, classification, and SAM or SAM2 segmentation.

- Skill: `newmindsgroup/hugging-face-vision-trainer` (Agent Skill, multi-file: 13 files)
- Install (CLI): `npx skillmds@latest add newmindsgroup/hugging-face-vision-trainer`
- Raw SKILL.md: https://api.skillmd.com/api/skills/newmindsgroup/hugging-face-vision-trainer/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: AI & ML
- License: MIT
- Author: newmindsgroup (https://skillmd.com/u/newmindsgroup)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/newmindsgroup/hugging-face-vision-trainer

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# Vision Model Training on Hugging Face Jobs

Train object detection, image classification, and SAM/SAM2 segmentation models on managed cloud GPUs. No local GPU setup required—results are automatically saved to the Hugging Face Hub.

## When to Use
- The request matches the skill description: Train or fine-tune vision models on Hugging Face Jobs for detection, classification, and SAM or SAM2 segmentation.
- The task needs the implementation patterns, examples, validation checks, or edge cases listed in the topic map.
- The work would benefit from the complete guidance preserved in `references/full-guidance.md`.

## Core Workflow
1. Confirm the request matches this skill's trigger, scope, and risk profile.
2. Use the topic map to identify the relevant pattern, checklist, or example before writing detailed guidance or code.
3. Load `references/full-guidance.md` when implementation details, examples, anti-patterns, validation checks, or edge cases are needed.
4. Apply only the relevant guidance instead of loading or repeating the entire reference by default.
5. Verify the result against any validation checks, limitations, security notes, or platform constraints in the reference.

## Topic Map
- When to Use This Skill
- Related Skills
- Local Script Execution
- Prerequisites Checklist
- Account & Authentication
- Dataset Requirements — Object Detection
- Dataset Requirements — Image Classification
- Dataset Requirements — SAM/SAM2 Segmentation
- Critical Settings
- Dataset Validation
- Running the Inspector
- Reading Results
- Automatic Bbox Preprocessing
- Training workflow
- Critical directives
- Job submission: `hf_jobs` MCP tool vs Python API
- Authentication via job secrets + explicit hub_token injection
- JobInfo attribute

## Reference Map
- `references/full-guidance.md` preserves the complete original guidance, including examples and detailed edge cases.

## Limitations
- Use this skill only when the task clearly matches the scope described above.
- Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
- Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.

## Progressive Loading
Keep this `SKILL.md` as the compact routing and workflow entrypoint. Load the reference file only when the user task requires the deeper implementation material.