sample.json

{
  "guid": "030C6A71-39DA-436E-9644-4FC25C7C5907",
  "name": "TensorFlow Fine-tuning and Inference for LLMs with Bfloat16",
  "categories": ["Toolkit/oneAPI AI And Analytics/Features and Functionality"],
  "description": "This sample illustrates how to fine-tune and do inference of a TensorFlow LLM model using Bfloat16",
  "builder": ["cli"],
  "languages": [{ "python": {} }],
  "os": ["linux"],
  "targetDevice": ["CPU"],
  "cpuInstructionSets": ["AVX512", "AMX"],
  "ciTests": {
    "linux": [{
      "env": [
        "source /intel/oneapi/intelpython/bin/activate",
        "conda activate tensorflow",
        "pip install uv",
        "uv init",
        "uv python pin $(which python)",
        "uv venv --system-site-packages",
        "uv add -r requirements.txt",
        "uv add py-cpuinfo nbformat nbconvert",
        "uv add --dev ipykernel",
        "uv run ipython kernel install --user --name tensorflow",
        "uv add notebook nbconvert"
      ],
      "id": "intel llm bf16 infrence and fine-tuning",
      "steps": [
        "uv run python GPTJ_finetuning.py",
        "uv run python ci_test.py"
      ]
    }]
  },
  "expertise": "Code Optimization"
}