Gradient AI LLM API FinetuningをAIに接続

• 01 / 02データの抽出方法
• 02 / 02モデルのファインチューニング方法

最速日

880ms

最遅日

1267ms

14日間の傾向

遅延傾向+7%

Gradient AI Connector

準備完了です。MCPクライアントを選択し、セットアップ手順に従ってください。

コネクタリンクhttps://edge.vinkius.com/vk_preview_KwJfHerXBfsWKXVQH8bGJG4HGUwUfVlRXkPpGPNU/mcpコピー

Claude Desktop

以下の手順で数秒で接続できます。

1. 1In Claude Desktop, open Settings → Connectors.
2. 2Click “Add custom connector” and paste the connector link above as the remote MCP server URL.
3. 3Click Add and start a new chat — Gradient AI capabilities are ready to use.

設定 · claude_desktop_config.jsonコピー

{
  "mcpServers": {
    "gradient-ai-llm-api-finetuning-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_KwJfHerXBfsWKXVQH8bGJG4HGUwUfVlRXkPpGPNU/mcp"
    }
  }
}

• Claude
• ChatGPT
• Cursor
• VS Code
• Windsurf
• Claude Code
• JetBrains
• Cline

各クライアントの手順ガイドはこちらです。 接続方法

Claude向けのガイド付きセットアップ？ Gradient AIをClaudeや他のAIに設定する

このConnectorが対応するすべてのAIクライアントを見る ↑

• 01

  AIエンジニア

  ファインチューニングの実験を迅速に繰り返し、モデルの回答精度をテストできます。

• 02

  データサイエンティスト

  複雑なローカル環境を構築することなく、埋め込みの生成やNLP分析を実行できます。

• 03

  開発者

  高度なLLM機能を、最小限の手間でアプリケーションに統合できます。

• 01

  How do I connect this MCP to my AI client?

  You subscribe to the MCP on Vinkius and connect your client once. After that, the capabilities are ready to use in Claude, Cursor, or Windsurf.

• 02

  What credentials do I need?

  You will need your Gradient API Key and your Workspace ID to authenticate the connection.

• 03

  Can I use my own fine-tuned models?

  Yes, you can list, create, and manage your custom fine-tuned model instances through the MCP.

• 04

  Does this support RAG?

  Yes, you can create RAG collections and generate embeddings for retrieval tasks.

• 05

  Can I process PDF files?

  Yes, the MCP includes capabilities to upload files and extract text or data from PDFs.

• 06

  How can I start training a custom model with my own data?

  You can use the fine_tune_model capability. Simply provide the model ID and an array of training samples. The agent will handle the submission to Gradient's training infrastructure.

• 07

  Can I use RAG (Retrieval Augmented Generation) with this server?

  Yes! The complete_model capability includes an optional rag parameter, allowing you to provide context or collection IDs to ground the model's responses in specific data.

• 08

  How do I generate vector embeddings for my documents?

  Use the generate_embeddings capability by specifying a model slug (like 'bge-large') and a list of text inputs. It will return the high-dimensional vectors for your text.

• 

  LLM Fine-Tuning Dataset Validator AIコネクタ

  Verify structural integrity, token distribution, and training costs of JSONL datasets.

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• 

  Predibase (LLM Serving & Finetuning) AIコネクタ

  Deploy and query fine-tuned LLMs via Predibase — run inference, classify text, and monitor deployment metrics

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• 

  Mistral AI (Frontier LLMs & Embeddings) AIコネクタ

  Manage AI inference via Mistral — execute chat completions, generate RAG embeddings, and audit frontier models

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• 

  OpenAI AIコネクタ

  Use GPT-4o, DALL-E 3, embeddings, fine-tuning, and moderation as tools inside your AI agent workflows.

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