> ## Documentation Index > Fetch the complete documentation index at: https://docs.monostate.ai/llms.txt > Use this file to discover all available pages before exploring further. # Wizard Commands > All commands and shortcuts available in the wizard # Wizard Commands Reference The AITraining wizard supports various commands to help you navigate, search, and configure your training job. ## Navigation Commands These commands work at any prompt: | Command | Shortcut | Description | | ------- | --------- | ----------------------------------------- | | `:back` | | Go back to the previous step | | `:help` | `?`, `:h` | Show detailed help for the current prompt | | `:exit` | `:quit` | Cancel the wizard and exit | ### Using :back You can go back at any point to change previous answers: ``` Model (number, HF ID, or command): :back ↩️ Going back to dataset selection... Dataset (number, HF ID, or command): ``` ### Using :help Every prompt has contextual help: ``` Training split name [train]: :help ℹ️ Help Dataset splits are named subsets of your data. Common split names: • 'train' - Training data (most common) • 'test' - Test/evaluation data • 'validation' or 'valid' - Validation data Note: This is NOT asking for a percentage split (like 80/20). It's asking for the exact name of the split in your dataset. Training split name [train]: ``` ## Catalog Commands These commands work when browsing models or datasets: | Command | Description | | ----------------- | --------------------------------------------------- | | `/search ` | Search for models/datasets by name | | `/sort` | Change sorting (trending, downloads, likes, recent) | | `/filter` | Filter models by size (models only) | | `/refresh` | Clear cache and reload the list | ### /search Find specific models or datasets: ``` Model (number, HF ID, or command): /search llama Popular models (trending): 1. meta-llama/Llama-3.2-1B (1B) 2. meta-llama/Llama-3.2-3B (3B) 3. meta-llama/Llama-3.1-8B (8B) 4. meta-llama/Llama-3.1-70B (70B) ... ``` Search examples: * `/search gemma` - Find Gemma models * `/search code` - Find code-focused models * `/search alpaca` - Find Alpaca-style datasets * `/search conversation` - Find conversation datasets ### /sort Change how results are ordered: ``` Model (number, HF ID, or command): /sort Sort options: [T]rending [D]ownloads [L]ikes [R]ecent Sort by [T]: D ``` | Sort Option | Key | Description | | ----------- | --- | --------------------------- | | Trending | T | What's popular right now | | Downloads | D | Most downloaded all-time | | Likes | L | Most liked by the community | | Recent | R | Newest additions | ### /filter Filter models by parameter count (only works for models, not datasets): ``` Model (number, HF ID, or command): /filter Filter size: [A]ll [S]mall(<3B) [M]edium(3-10B) [L]arge(>10B) Filter size [A]: S ``` | Filter | Key | Size Range | Typical Hardware | | ------ | --- | ------------------- | ----------------------- | | All | A | No filter | Any | | Small | S | \< 3B parameters | MacBook, consumer GPU | | Medium | M | 3B - 10B parameters | Gaming GPU, workstation | | Large | L | > 10B parameters | Cloud GPU, multi-GPU | ### /refresh Clear the cache and fetch fresh data: ``` Model (number, HF ID, or command): /refresh Cache cleared. Popular models (trending): ... ``` ## Selection Methods When choosing a model or dataset, you have several options: ### By Number Select from the displayed list: ``` Popular models (trending): 1. google/gemma-3-270m (270M) 2. google/gemma-2-2b (2B) 3. meta-llama/Llama-3.2-1B (1B) Model (number, HF ID, or command): 2 ✓ Model: google/gemma-2-2b ``` ### By HuggingFace ID Type the full model/dataset ID: ``` Model (number, HF ID, or command): mistralai/Mistral-7B-v0.3 ✓ Model: mistralai/Mistral-7B-v0.3 ``` ### By Local Path Point to a local directory: ``` Dataset (number, HF ID, or command): ./my_training_data ✓ Dataset: ./my_training_data ``` ## Input Conventions ### Defaults Values in `[brackets]` are defaults. Press Enter to accept: ``` Project name [my-llm-project]: ↵ ✓ Project: my-llm-project ``` ### Required Fields Fields marked `[REQUIRED]` must be filled: ``` Prompt column name [REQUIRED] [prompt]: ↵ ❌ This field is required for DPO/ORPO training. Prompt column name [REQUIRED] [prompt]: instruction ✓ ``` ### Yes/No Questions Answer with y/yes or n/no: ``` Configure advanced parameters? [y/N]: y Enable LoRA? [Y/n]: ↵ ✓ LoRA enabled (default) ``` Capitalized letter indicates the default: * `[Y/n]` - Default is Yes * `[y/N]` - Default is No ## Keyboard Shortcuts | Key | Action | | ------------- | ---------------------------------------------- | | Enter | Accept default or confirm input | | Ctrl+C | Cancel wizard (same as `:exit`) | | Arrow Up/Down | Scroll through numbered options (if supported) | ## Advanced Parameters When configuring advanced parameters, the wizard groups them: ``` ⚙️ Training Hyperparameters Configure Training Hyperparameters parameters? [y/N]: y epochs [1]: batch_size [2]: lr [3e-5]: ``` Each group can be configured independently: | Group | Contains | | ------------------------ | ---------------------------------------- | | Training Hyperparameters | epochs, batch\_size, lr, warmup\_ratio | | PEFT/LoRA | peft, lora\_r, lora\_alpha, quantization | | DPO/ORPO | dpo\_beta, max\_prompt\_length | | Hub Integration | push\_to\_hub, username, token | | Knowledge Distillation | teacher\_model, distill\_temperature | | Hyperparameter Sweep | use\_sweep, sweep\_n\_trials | | Enhanced Evaluation | use\_enhanced\_eval, eval\_metrics | | Reinforcement Learning | rl\_reward\_model\_path (PPO only) | ## Tips Every single prompt has detailed help. If you're unsure what something means, type `:help`. Made a wrong choice? Use `:back` to return to previous steps. Your other answers are preserved. Instead of scrolling through hundreds of models, use `/search llama` or `/search 7b` to narrow down. Not sure which models will work? Use `/filter` → `S` (small) to see only models that fit consumer hardware. On your first training, accept most defaults. Get something working, then customize. ## Command Quick Reference ``` # Navigation :back Go to previous step :help Show help for current prompt :exit Cancel and exit # Catalog (models/datasets) /search query Search by name /sort Change sort order /filter Filter by size (models only) /refresh Reload list # Selection 1, 2, 3... Select by number google/gemma Type HuggingFace ID ./my_data Type local path # Input Enter Accept default y/n Yes/No answers Ctrl+C Cancel ```