Package index
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dragon_check() - Check the Python environment and hardware
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dragon_python_requirements() - Python requirements used by dragonfarm
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dragon_presets() - Recommended small models
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dragon_dataset() - Create a dataset for fine-tuning
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dragon_map() - Map dataset columns to prompt, response, and system text
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dragon_map_pairs() - Map columns for preference optimization
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dragon_map_prompts() - Map columns for reinforcement learning
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dragon_conversations() - Multi-turn conversations as training data
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dragon_synthesize() - Write fine-tuning data with a teacher model
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dragon_synthesize_pairs() - Build preference pairs from a model's own samples
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dragon_prompts() - Prompts from a run's data files
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dragon_preview() - Preview mapped rows as chat turns
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dragon_split() - Hold out rows for evaluation
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dragon_example_data() - Path to the bundled example dataset
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dragon_lora() - LoRA settings
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dragon_train_args() - Training settings
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dragon_hardware() - Hardware settings
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dragon_train() - Fine-tune a model with LoRA
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dragon_prefer() - Preference optimization with DPO or ORPO
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dragon_reinforce() - Reinforcement learning with verifiable rewards (GRPO)
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dragon_reward() - Verifiable rewards for reinforcement learning
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dragon_resume() - Resume a run from its latest checkpoint
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dragon_wait() - Wait for a run to finish
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dragon_cancel() - Cancel a run
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dragon_run() - Reopen an existing run
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dragon_runs() - List runs
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dragon_archived_runs() - Archived runs
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dragon_archive_run()dragon_unarchive_run()dragon_delete_run() - Archive, restore, or delete a run
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dragon_runs_dir() - Directory where runs are stored
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dragon_status()dragon_progress()dragon_logs() - Inspect a run
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dragon_code() - R code that reproduces a run
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dragon_evaluate() - Evaluate a finished run
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dragon_metrics()dragon_metric_regex() - Task metrics for generated replies
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dragon_judge() - Judge a run's replies with a language model
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dragon_llm_anthropic()dragon_judge_anthropic()dragon_llm_ellmer()dragon_judge_ellmer() - Language models as functions: the Claude API and ellmer
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dragon_compare() - Compare runs side by side
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dragon_backend_local()dragon_backend_server()dragon_backend_ollama()dragon_backend() - Inference backends
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dragon_serve_ollama() - Serve a run's model with Ollama
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dragon_worker_stop() - Stop the local inference worker
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dragon_chat()dragon_chat_load() - Talk to a model, with memory of the conversation
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dragon_feedback() - Training data from chat feedback
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dragon_generate() - Generate replies from a fine-tuned model
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dragon_merge() - Merge the adapter into the base model
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dragon_export_gguf() - Export a merged model to GGUF
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dragon_publish() - Push a run's model to the Hugging Face Hub
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dragon_pipeline() - Run several post-training stages as one pipeline
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dragon_step_train()dragon_step_prefer()dragon_step_synthesize_pairs()dragon_step_reinforce()dragon_step_judge()dragon_step_evaluate()dragon_step_merge()dragon_step_publish() - Steps of a post-training pipeline
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dragon_pipeline_status() - Progress of a pipeline
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dragon_pipeline_cancel() - Cancel a pipeline
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dragon_bundle() - Package a run for a cloud GPU
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dragon_remote() - Open a cloud GPU provider for a bundled run
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dragon_import() - Import results trained on another machine
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dragon_remote_providers() - Cloud GPU providers
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dragon_app() - Launch the dragon-farm app