CLI tool for interacting with the Felafax platform; fine-tuning and inference on non-NVIDIA chipsets.
Project description
Felafax CLI
A command-line interface for fine-tuning and managing large language models.
Installation
pip install felafax-cli
Quick Start
- Login with your authentication token:
felafax-cli auth login --token <your-token>
- Initialize a fine-tuning configuration:
felafax-cli tune init-config
- Upload your training data:
felafax-cli files upload path/to/data.jsonl
- Start fine-tuning:
felafax-cli tune start --model <model_name> --config config.yml --dataset <dataset_id>
Available Commands
Authentication
# Login with your token
felafax-cli auth login --token <your-token> [--force]
Model Management
# List available fine-tuned models
felafax-cli model list
# Start an interactive chat session with a model
felafax-cli model chat <model_id> [--system-prompt "Your custom prompt"]
# Get detailed information about a model
felafax-cli model info <model_id>
# Delete a fine-tuned model
felafax-cli model delete <model_id>
Training Management
# Initialize a new config file
felafax-cli tune init-config
# Start a new fine-tuning job
felafax-cli tune start \
--model <model_name> \
--config path/to/config.yml \
--dataset <dataset_id>
# 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 in storage
felafax-cli files list [--prefix <prefix>] [--limit <number>]
# Upload training data
felafax-cli files upload <file_path>
# Delete a file
felafax-cli files delete <file_path>
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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