Generate Python scripts for Supervised Fine-Tuning of language models in the ART framework.
npx skills add https://github.com/OpenPipe/ART --skill train-sft
Please help me install this Agent Skill. Skill: train-sft Source: https://github.com/OpenPipe/ART/tree/main/.agents/skills/train-sft Command: npx skills add https://github.com/OpenPipe/ART --skill train-sft
This Skill helps users fine-tune language models using Supervised Fine-Tuning (SFT) with the ART framework, enabling them to create custom models for specific tasks.
Use the train-sft skill to start a new SFT training process.
High-intent search queries and answers about installing and using this skill.
To start supervised fine-tuning (SFT) using the ART framework, you select your training data, choose a backend, configure hyperparameters, and generate a runnable Python script. The process guides you through customizing models for specific applications.
Yes, you can train using either a ServerlessBackend for managed GPUs or a LocalBackend for your local GPU. Both backend options are supported when configuring your supervised fine-tuning environment.
Supervised fine-tuning supports training directly from JSONL files or using distillation from a teacher model. You can choose either data source when setting up your training script.
The best way to create a specialized chatbot is by fine-tuning a base language model on a dataset of past customer interactions. This supervised fine-tuning process adapts the model specifically for your customer support tasks.
Yes, the supervised fine-tuning process guides you through selecting data and configuring hyperparameters to automatically generate a runnable Python script. This script executes the training using the ART framework.
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