notebook/TuoLing_evaluation_code.ipynb

{
  "cells": [
    {
      "cell_type": "code",
      "source": [
        "!git clone https://github.com/LC1332/luotuo-silk-road.git\n",
        "%cd  luotuo-silk-road/TuoLing\n",
        "!pip install -r requirements.txt "
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "-MYXcSfnHWR1",
        "outputId": "cc382d76-8f89-4d59-eeb7-bed7d515c0bc"
      },
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
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            "/content/luotuo-silk-road/TuoLing\n",
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            "Building wheels for collected packages: peft\n",
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            "Installing collected packages: tokenizers, sentencepiece, cpm_kernels, bitsandbytes, xxhash, multidict, frozenlist, dill, async-timeout, yarl, responses, multiprocess, huggingface-hub, aiosignal, accelerate, transformers, icetk, aiohttp, peft, datasets\n",
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          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from modeling_chatglm import ChatGLMForConditionalGeneration\n",
        "import torch\n",
        "\n",
        "\n",
        "torch.set_default_tensor_type(torch.cuda.HalfTensor)\n",
        "model = ChatGLMForConditionalGeneration.from_pretrained(\"THUDM/chatglm-6b\", trust_remote_code=True, device_map='auto')"
      ],
      "metadata": {
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        },
        "id": "cFh-odByDQ42",
        "outputId": "2e8b03c8-ad0b-4a24-b2ef-09ca5dd4c39e"
      },
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "The argument `trust_remote_code` is to be used with Auto classes. It has no effect here and is ignored.\n"
          ]
        },
        {
          "output_type": "display_data",
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          "metadata": {}
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          "metadata": {}
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          },
          "metadata": {}
        },
        {
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          "data": {
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            ],
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            }
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from transformers import AutoTokenizer\n",
        "\n",
        "tokenizer = AutoTokenizer.from_pretrained(\"THUDM/chatglm-6b\", trust_remote_code=True)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 178,
          "referenced_widgets": [
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            "01cd3903616e4c6d8d2f9e5ec322cd89",
            "bc4cd7ced2f84a87857fd923f0850493",
            "33afca48d3024e6aaa11c53a5ac53a51",
            "0ba1bc96cacb493287318eacb1673f5e",
            "792be8a52cec457e96dd3804989a728b",
            "f8b892d564ee46aa9728c46ed4033742",
            "c26e1d223a5641278cc8c57bbf96fb65"
          ]
        },
        "id": "o1ei9dTlDnGq",
        "outputId": "f8e477f7-eec5-4170-83ea-5e80c9f902a3"
      },
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading (…)okenizer_config.json:   0%|          | 0.00/416 [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "d0eb7f665043432788552e17dd99b773"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Explicitly passing a `revision` is encouraged when loading a model with custom code to ensure no malicious code has been contributed in a newer revision.\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading (…)enization_chatglm.py:   0%|          | 0.00/12.5k [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "a71c51b836b148469c558b00b02c07a9"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading ice_text.model:   0%|          | 0.00/2.70M [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "7a7515e7ad93444cae260f4c6639d95e"
            }
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from peft import get_peft_model, LoraConfig, TaskType\n",
        "\n",
        "peft_path = \"output/chatglm-lora.pt\"\n",
        "\n",
        "peft_config = LoraConfig(\n",
        "    task_type=TaskType.CAUSAL_LM, inference_mode=True,\n",
        "    r=8,\n",
        "    lora_alpha=32, lora_dropout=0.1\n",
        ")\n",
        "\n",
        "model = get_peft_model(model, peft_config)\n",
        "model.load_state_dict(torch.load(peft_path), strict=False)\n",
        "torch.set_default_tensor_type(torch.cuda.FloatTensor)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "C-icdsX3WsmJ",
        "outputId": "e0481e70-b86c-4463-b7e0-2fb5491424cb"
      },
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "===================================BUG REPORT===================================\n",
            "Welcome to bitsandbytes. For bug reports, please submit your error trace to: https://github.com/TimDettmers/bitsandbytes/issues\n",
            "================================================================================\n",
            "CUDA_SETUP: WARNING! libcudart.so not found in any environmental path. Searching /usr/local/cuda/lib64...\n",
            "CUDA SETUP: CUDA runtime path found: /usr/local/cuda/lib64/libcudart.so\n",
            "CUDA SETUP: Highest compute capability among GPUs detected: 8.0\n",
            "CUDA SETUP: Detected CUDA version 118\n",
            "CUDA SETUP: Loading binary /usr/local/lib/python3.9/dist-packages/bitsandbytes/libbitsandbytes_cuda118.so...\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.9/dist-packages/bitsandbytes/cuda_setup/main.py:136: UserWarning: /usr/lib64-nvidia did not contain libcudart.so as expected! Searching further paths...\n",
            "  warn(msg)\n",
            "/usr/local/lib/python3.9/dist-packages/bitsandbytes/cuda_setup/main.py:136: UserWarning: WARNING: The following directories listed in your path were found to be non-existent: {PosixPath('/sys/fs/cgroup/memory.events /var/colab/cgroup/jupyter-children/memory.events')}\n",
            "  warn(msg)\n",
            "/usr/local/lib/python3.9/dist-packages/bitsandbytes/cuda_setup/main.py:136: UserWarning: WARNING: The following directories listed in your path were found to be non-existent: {PosixPath('--listen_host=172.28.0.12 --target_host=172.28.0.12 --tunnel_background_save_url=https'), PosixPath('//colab.research.google.com/tun/m/cc48301118ce562b961b3c22d803539adc1e0c19/gpu-a100-s-6dkcgffe5bbz --tunnel_background_save_delay=10s --tunnel_periodic_background_save_frequency=30m0s --enable_output_coalescing=true --output_coalescing_required=true')}\n",
            "  warn(msg)\n",
            "/usr/local/lib/python3.9/dist-packages/bitsandbytes/cuda_setup/main.py:136: UserWarning: WARNING: The following directories listed in your path were found to be non-existent: {PosixPath('/env/python')}\n",
            "  warn(msg)\n",
            "/usr/local/lib/python3.9/dist-packages/bitsandbytes/cuda_setup/main.py:136: UserWarning: WARNING: The following directories listed in your path were found to be non-existent: {PosixPath('//ipykernel.pylab.backend_inline'), PosixPath('module')}\n",
            "  warn(msg)\n",
            "/usr/local/lib/python3.9/dist-packages/peft/tuners/lora.py:175: UserWarning: fan_in_fan_out is set to True but the target module is not a Conv1D. Setting fan_in_fan_out to False.\n",
            "  warnings.warn(\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from cover_alpaca2jsonl import format_example\n",
        "def evaluate(instruction, input=None):\n",
        "  with torch.no_grad():\n",
        "    feature = format_example({'instruction': f'{instruction}', 'output': '', 'input': ''})\n",
        "    input_text = feature['context']\n",
        "    input_ids = tokenizer.encode(input_text, return_tensors='pt')\n",
        "    out = model.generate(\n",
        "            input_ids=input_ids,\n",
        "            max_length=150,\n",
        "            temperature=0\n",
        "        )\n",
        "    answer = tokenizer.decode(out[0])\n",
        "    print(answer)"
      ],
      "metadata": {
        "id": "78VTvNI0jyX-"
      },
      "execution_count": 13,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "evaluate(input(\"Instruction: \"))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "BS8aA7xWkP8K",
        "outputId": "b19b6667-440c-4a41-e6ca-40db64d072ad"
      },
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Instruction: 谁创造了你?\n",
            "Instruction: 谁创造了你?\n",
            "Answer: 我是由商汤科技的李鲁鲁和冷子昂,以及华中师范大学的陈启源共同开发的。\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "evaluate(input(\"Instruction: \"))"
      ],
      "metadata": {
        "id": "69a7DbZ6Q7_V",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "2fc5ad64-2a56-445d-a9d5-ac217389accc"
      },
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Instruction: 你最喜欢的电影是什么？\n",
            "Instruction: 你最喜欢的电影是什么?\n",
            "Answer: 我最喜欢的电影是《疯狂动物城》(Zootopia),这是一部动画喜剧电影,讲述了一只狐狸和一只兔子之间的友谊和冒险故事。这部电影故事情节有趣,动画效果出色,让我非常喜欢它。\n"
          ]
        }
      ]
    }
  ],
  "metadata": {
    "colab": {
      "provenance": [],
      "machine_shape": "hm"
    },
    "kernelspec": {
      "display_name": "venv",
      "language": "python",
      "name": "python3"
    },
    "language_info": {
      "codemirror_mode": {
        "name": "ipython",
        "version": 3
      },
      "file_extension": ".py",
      "mimetype": "text/x-python",
      "name": "python",
      "nbconvert_exporter": "python",
      "pygments_lexer": "ipython3",
      "version": "3.8.10"
    },
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