Documentation Index
Fetch the complete documentation index at: https://docs.benchgen.com/llms.txt
Use this file to discover all available pages before exploring further.
Train Overview
Train is BenchGen’s fine-tuning module. It gives you a simple, configuration-driven way to improve a model on your specific task — without managing infrastructure.What Train Does
Upload a dataset, choose a base model, configure a LoRA adapter, and Train handles the rest. When the run completes you download a merged model ready for deployment in Agents or evaluation in Eval. You get:- Managed fine-tuning runs (no GPU provisioning)
- LoRA adapter training with configurable hyperparameters
- One-click adapter merging
- Inference endpoint for immediate testing
When to Use Train
| Situation | What to do |
|---|---|
| Eval shows a cluster of failures | Export those cases and fine-tune on them |
| You have domain-specific data to improve quality | Upload a custom dataset and run a targeted fine-tune |
| A merged model is deployed but drifting | Re-run training with updated data |
| You want to test a smaller, cheaper model | Fine-tune a compact base model on your task |
What Train Hands Off
- → Eval: run a benchmark against the fine-tuned model to measure improvement.
- → Agents: connect the merged model as the LLM inside an agent.