List fine-tuning training jobs on Tuning Engines. Returns recent jobs with status, base model, agent type, GPU usage, and cost. Use this to check on existing training runs or find a job ID.

Get full details of a specific fine-tuning job including status, base model, agent type, GPU minutes, cost, error messages, and whether it can be retried from checkpoint.

Fine-tune an LLM on a GitHub repository using Tuning Engines. This trains a custom model that learns from the code patterns, style, and conventions in the repo. Choose an agent to control the training approach:

AVAILABLE AGENTS:

• agent='code_repo' (Cody) — LoRA-based code fine-tuning using QLoRA (4-bit quantized LoRA) via the Axolotl framework. Trains on your repo's code patterns, naming conventions, and project structure to produce a fast, lightweight adapter. Best for: code autocomplete, inline suggestions, tab-complete, code style matching.

• agent='sera_code_repo' (SIERA) — Bug-fix specialist using the Open Coding Agents approach from AllenAI. Generates synthetic error-resolution training pairs from your repo, producing a model that understands your codebase's failure patterns and fix conventions. Best for: debugging, error resolution, patch generation, root cause analysis. Supports quality_tier='low' (faster) or quality_tier='high' (deeper analysis, more training data).

SUPPORTED BASE MODELS (by size):

• 3B: Qwen/Qwen2.5-Coder-3B-Instruct

• 7-8B: codellama/CodeLlama-7b-hf, deepseek-ai/deepseek-coder-7b-instruct-v1.5, Qwen/Qwen2.5-Coder-7B-Instruct, Qwen/Qwen3-8B

• 13-15B: codellama/CodeLlama-13b-Instruct-hf, bigcode/starcoder2-15b, Qwen/Qwen2.5-Coder-14B-Instruct, Qwen/Qwen3-14B

• 22-27B: mistralai/Codestral-22B-v0.1, google/gemma-2-27b

• 30-34B: deepseek-ai/deepseek-coder-33b-instruct, codellama/CodeLlama-34b-Instruct-hf, Qwen/Qwen2.5-Coder-32B-Instruct, Qwen/Qwen3-Coder-30B-A3B, Qwen/Qwen3-32B

• 70-72B: codellama/CodeLlama-70b-Instruct-hf, meta-llama/Llama-3.1-70B-Instruct, Qwen/Qwen2.5-72B-Instruct

TYPICAL WORKFLOW: estimate_job first to check cost, then create_job, then job_status to monitor progress.

Cancel a running or queued fine-tuning job. The job will be charged for any GPU time already used.

Get live status of a fine-tuning job including current status, GPU minutes used, estimated charges, remaining balance, and delivery progress. Use this to monitor a running job.

Retry a failed fine-tuning job from its last checkpoint. Creates a new job that resumes training where the failed one stopped, saving GPU time. Each retry is billed separately.

IMPORTANT: This tool fetches a cost estimate and includes it in the response. You MUST show the estimate to the user and get their explicit approval before considering the retry confirmed. The retry is submitted automatically (the server validates balance), but always present the cost to the user.

Get a cost estimate for a fine-tuning job before submitting it. Returns estimated cost, cost range, current balance, and whether balance is sufficient. Always estimate before creating a job.

Validate S3 credentials by testing read/write access to the specified bucket. Use before submitting a job with S3 export.

List your trained and imported models on Tuning Engines.

Get details of a specific trained model.

Delete a trained model from cloud storage.

Check your Tuning Engines account balance and recent transactions.

Get your Tuning Engines account details and settings.

List the supported base HuggingFace models available for fine-tuning on Tuning Engines. Optionally filter by agent to see only compatible models.

Import a model from S3 into Tuning Engines cloud storage so it can be used as a base for future fine-tuning jobs.

Export a trained model from Tuning Engines cloud storage to your S3 bucket.

Check the status of a model import or export operation.

List available pre-built models and datasets from the Tuning Engines Marketplace. These are platform-owned, ready-to-use assets that can be exported to your S3 bucket. Returns name, description, base model, size, export price, and category.

Get detailed information about a specific pre-built model or dataset from the Marketplace including description, pricing, and export options.

Export a pre-built model or dataset from the Marketplace to your S3 bucket. Credits will be charged based on the export price upon successful completion.

Check the status of a Marketplace export operation. Returns status, charge info, and any error messages.

List datasets available for training and evaluation. Datasets can be uploaded from S3 and used for fine-tuning or model evaluation.

Get details of a specific dataset including status, source, and metadata.

Create a new dataset by importing from S3. Datasets can be used for fine-tuning or model evaluation.

Delete a dataset from the platform.

Check the status of a dataset import or processing operation.

List model evaluations. Evaluations run your trained models against benchmark datasets using various evaluators to measure quality.

Get full details of a specific evaluation including status, scores, metrics, and comparison data.

Create a new model evaluation. Run your trained model or a base model against a dataset using selected evaluators. Use list_evaluators to see available evaluators (e.g. code_execution, similarity, llm_judge).

Cancel a running or queued evaluation.

Get live status of an evaluation including progress and current metrics.

List available evaluators for model evaluation. Evaluators measure different aspects of model quality like code execution, similarity, or LLM-based judgment.

Get a cost estimate for an evaluation before running it.

List models available for inference through the Tuning Engines inference API. Includes both platform models and your deployed trained models.

Get inference API usage statistics including request counts, token usage, and costs.

Get a JWT token for authenticating with the Tuning Engines inference API. Use this to make direct API calls to the inference endpoint.

List available agents configured for your organization. Agents are AI assistants with specific capabilities and tool access.

Get details of a specific agent including capabilities, tools, and configuration.