Local-Inferencing_LlaMa-2.ipynb

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      "source": [
        "### Checkout my [Twitter(@rohanpaul_ai)](https://twitter.com/rohanpaul_ai) for daily LLM bits"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "PH68I6NAedUb"
      },
      "outputs": [],
      "source": [
        "!pip install -qU transformers"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "The Pipeline mainly defines the following:\n",
        "\n",
        "- The specific LLM, in this case it will be 'meta-llama/Llama-2-7b-hf'\n",
        "- The respective tokenizer for the model\n",
        "- access_token for your HuggingFace"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "r_Od3Bc1e6vJ"
      },
      "outputs": [],
      "source": [
        "from torch import cuda\n",
        "import transformers"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {},
      "outputs": [],
      "source": [
        "model_id = 'meta-llama/Llama-2-7b-hf'"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {},
      "outputs": [],
      "source": [
        "cuda.is_available()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {},
      "outputs": [],
      "source": [
        "device = f'cuda:{cuda.current_device()}' if cuda.is_available() else 'cpu'\n",
        "device"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {},
      "outputs": [],
      "source": [
        "from huggingface_hub import login\n",
        "\n",
        "access_token_read = \"Your HuggingFace API\"\n",
        "\n",
        "login(token = access_token_read)\n",
        "\n",
        "# Alternative way to login to HuggingFace\n",
        "#!huggingface-cli login"
      ]
    },
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      "outputs": [],
      "source": [
        "tokenizer = transformers.AutoTokenizer.from_pretrained(\n",
        "    model_id\n",
        ")"
      ]
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      "source": [
        "generate_text = transformers.pipeline(\n",
        "    model='meta-llama/Llama-2-7b-hf',\n",
        "    tokenizer=tokenizer,\n",
        "    task='text-generation',\n",
        "    temperature=0.0,  # 'randomness' of outputs, 0.0 is the min and 1.0 the max\n",
        "    max_new_tokens=512,  # mex number of tokens to generate in the output\n",
        "    repetition_penalty=1.1  # without this output begins repeating\n",
        ")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {},
      "outputs": [],
      "source": [
        "res = generate_text(\"Explain to me the difference between nuclear fission and fusion.\")\n",
        "\n",
        "print(res[0][\"generated_text\"])"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "\"\\nNuclear fission is a process in which an atomic nucleus splits into two or more smaller nuclei, releasing a large amount of energy in the process. This occurs when an atom's nucleus is bombarded with a high-energy particle, such as a neutron. Fission is the process used in nuclear power plants to generate electricity.\\nNuclear fusion, on the other hand, is the process by which two or more atomic nuclei combine to form a single, heavier nucleus."
      ]
    }
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