CLI tool for interacting with the Felafax platform; fine-tuning and inference on non-NVIDIA chipsets.
Project description
title: 'CLI Reference' description: 'Command-line interface for fine-tuning and managing large language models'
Installation
Install the Felafax CLI using pip:
pip install felafax-cli
Authentication
Before using the CLI, authenticate with your token:
felafax-cli auth login --token <your-token>
Use the `--force` flag to override existing authentication.
Core Features
Model Management
List Models
View all your available fine-tuned models:
felafax-cli model list
Interactive Chat
Start an interactive chat session with a model:
felafax-cli model chat <model_id> [--system-prompt "Your custom prompt"]
Model Information
Get detailed information about a specific model:
felafax-cli model info <model_id>
Delete Model
Remove a fine-tuned model:
felafax-cli model delete <model_id>
Training Management
Initialize Configuration
Create a new configuration file:
felafax-cli tune init-config
Start Fine-tuning
Launch a new fine-tuning job:
felafax-cli tune start \
--model <model_name> \
--config path/to/config.yml \
--dataset <dataset_id>
Manage Jobs
# List all training jobs
felafax-cli tune list
# Check job status
felafax-cli tune status --job-id <id>
# Stop a running job
felafax-cli tune stop --job-id <id>
File Management
List Files
View all your training data files:
felafax-cli files list [--prefix <prefix>] [--limit <number>]
Upload File
Upload a new training data file:
felafax-cli files upload <file_path>
Delete File
Remove a training data file:
felafax-cli files delete <file_path>
Configuration
Configuration Example
When you run felafax-cli tune init-config, it creates a YAML file with the following structure:
hyperparameters:
learning_rate: 1.0e-05
batch_size: 32
n_epochs: 4
warmup_ratio: 0.0
lora:
enabled: false
r: 8
alpha: 8
dropout: 0.0
Support
For more information, visit our documentation at https://docs.felafax.ai
License
MIT License
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