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It creates a light wrapper around transformers for inference.\n", "\n", "Note: Recently Outlines went through a v1.0.0 release 🔥" ], "metadata": { "id": "9K_Y2k8Zd2kF" } }, { "cell_type": "code", "execution_count": 6, "metadata": { "id": "2M4RVq1oaFR1" }, "outputs": [], "source": [ "!pip install -q --upgrade outlines transformers pydantic" ] }, { "cell_type": "markdown", "source": [ "# Load the model\n", "\n", "In this case we choose Qwen 4B and we'll use it to showcase the capabilities." ], "metadata": { "id": "Zwbg0G5Iebqw" } }, { "cell_type": "code", "source": [ "import outlines\n", "from transformers import AutoTokenizer, AutoModelForCausalLM\n", "\n", "\n", "MODEL_NAME = \"Qwen/Qwen3-4B\"\n", "model = outlines.from_transformers(\n", " AutoModelForCausalLM.from_pretrained(MODEL_NAME,\n", " device_map=\"auto\",\n", " torch_dtype=\"auto\"),\n", " AutoTokenizer.from_pretrained(MODEL_NAME)\n", ")" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 510, 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"stream", "name": "stderr", "text": [ "/usr/local/lib/python3.11/dist-packages/huggingface_hub/utils/_auth.py:104: UserWarning: \n", "Error while fetching `HF_TOKEN` secret value from your vault: 'Requesting secret HF_TOKEN timed out. Secrets can only be fetched when running from the Colab UI.'.\n", "You are not authenticated with the Hugging Face Hub in this notebook.\n", "If the error persists, please let us know by opening an issue on GitHub (https://github.com/huggingface/huggingface_hub/issues/new).\n", " warnings.warn(\n" ] }, { "output_type": "display_data", "data": { "text/plain": [ "config.json: 0%| | 0.00/726 [00:00