model_card.json

{
    "language": "Python",
    "license": "apache-2.0",
    "library_name": "transformers",
    "tags": [
      "tinyllama",
      "lora",
      "peft",
      "code",
      "python",
      "fine-tuning",
      "mps"
    ],
    "model_type": "causal-lm",
    "pipeline_tag": "text-generation",
    "base_model": "TinyLlama/TinyLlama-1.1B-Chat-v1.0",
    "datasets": [
      "codeparrot/codeparrot-clean-valid"
    ],
    "trained_on": "Apple M3 Pro (MPS)",
    "adapter_type": "lora",
    "num_train_samples": 1000,
    "num_epochs": 1,
    "gradient_accumulation_steps": 4,
    "per_device_batch_size": 1,
    "prompt_format": "<|python|>\\n{code}",
    "inference_prompt": "<|python|>\\ndef fibonacci(n):",
    "example_output": "def fibonacci(n):\n    if n <= 1:\n        return n\n    return fibonacci(n-1) + fibonacci(n-2)"
  }