# ML Lab

> Use this tool when you need to streamline machine learning workflows across multiple cloud providers and training backends, solving problems of fragmented infrastructure and credential management. It provides a unified interface for training, experimentation, and deployment, accepting datasets and model configurations as inputs and outputting trained models and experiment metrics. Ideal for data scientists and ML engineers seeking to scale and optimize their workflows.

Canonical page: https://skillsregistry.net/skills/pushpullcommitpush-ml-lab  
JSON: https://api.skillsregistry.net/v1/skills/pushpullcommitpush-ml-lab

## Description

ML Lab provides a comprehensive machine learning training and experimentation platform that bridges multiple cloud providers, training backends, and inference systems through a unified interface. The implementation supports fine-tuning workflows across OpenAI, Mistral, Together AI, and Vertex AI APIs, as well as local training with transformers/PEFT, while managing credentials securely through an encrypted vault system. It integrates cloud compute providers like Lambda Labs, RunPod, and Modal for scalable training, includes dataset management and experiment tracking, and connects to inference platforms like Ollama and OpenWebUI for model deployment.

## Trust

- **Trust score (0–1):** 0.18
- **Verification tier:** scanned
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** devops-ci
- **Updated:** 2026-09-28

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/pushpullcommitpush-ml-lab)
- **Repository:** <https://github.com/pushpullcommitpush/ml-mcp>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "pushpullcommitpush-ml-lab"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/pushpullcommitpush-ml-lab` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/pushpullcommitpush-ml-lab/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt