INTELLECT_1_Instruct_GGUF.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/Troyanovsky/Local-LLM-Comparison-Colab-UI/blob/main/INTELLECT_1_Instruct_GGUF.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "XNkpBtLvuTOp"
      },
      "source": [
        "## INTELLECT-1-Instruct-GGUF WebUI\n",
        "\n",
        "1. Run the following cell, takes ~5 min\n",
        "(You may need to confirm to proceed by typing \"Y\")\n",
        "2. Click the gradio link at the bottom\n",
        "\n",
        "\n",
        "Quantized model: https://huggingface.co/lmstudio-community/INTELLECT-1-Instruct-GGUF\n",
        "\n",
        "Original model: https://huggingface.co/PrimeIntellect/INTELLECT-1-Instruct\n",
        "\n",
        "Want to try other local LLMs? Check out this repo: https://github.com/Troyanovsky/Local-LLM-Comparison-Colab-UI/"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "D-MiHp_bveP6",
        "outputId": "90d9efee-c4b1-41fe-deff-dd9ec1e2f5a9"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
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            "\n",
            "You are in 'detached HEAD' state. You can look around, make experimental\n",
            "changes and commit them, and you can discard any commits you make in this\n",
            "state without impacting any branches by switching back to a branch.\n",
            "\n",
            "If you want to create a new branch to retain commits you create, you may\n",
            "do so (now or later) by using -c with the switch command. Example:\n",
            "\n",
            "  git switch -c <new-branch-name>\n",
            "\n",
            "Or undo this operation with:\n",
            "\n",
            "  git switch -\n",
            "\n",
            "Turn off this advice by setting config variable advice.detachedHead to false\n",
            "\n",
            "/content/text-generation-webui\n",
            "Ignoring llama-cpp-python: markers 'platform_system == \"Linux\" and platform_machine == \"x86_64\" and python_version == \"3.11\"' don't match your environment\n",
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            "  Downloading https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/cpu/llama_cpp_python-0.3.1+cpuavx2-cp310-cp310-linux_x86_64.whl (3.4 MB)\n",
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            "  Downloading https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/textgen-webui/llama_cpp_python_cuda-0.3.1+cu121-cp310-cp310-linux_x86_64.whl (449.5 MB)\n",
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            "  Downloading https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/textgen-webui/llama_cpp_python_cuda_tensorcores-0.3.1+cu121-cp310-cp310-linux_x86_64.whl (486.2 MB)\n",
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            "Collecting flash-attn==2.6.3+cu123torch2.4cxx11abiFALSE (from -r requirements.txt (line 61))\n",
            "  Downloading https://github.com/Dao-AILab/flash-attention/releases/download/v2.6.3/flash_attn-2.6.3+cu123torch2.4cxx11abiFALSE-cp310-cp310-linux_x86_64.whl (187.3 MB)\n",
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            "\u001b[?25hInstalling collected packages: pydub, xxhash, websockets, uvicorn, tomlkit, semantic-version, ruff, python-multipart, pydantic-core, Pillow, ninja, markupsafe, llvmlite, fsspec, ffmpy, diskcache, dill, cramjam, colorama, aiofiles, tiktoken, starlette, SpeechRecognition, pydantic, numba, multiprocess, sse-starlette, llama-cpp-python-cuda-tensorcores, llama-cpp-python-cuda, llama-cpp-python, gradio-client, fastparquet, fastapi, flask_cloudflared, flash-attn, exllamav2, bitsandbytes, accelerate, peft, gradio, datasets\n",
            "  Attempting uninstall: pydantic-core\n",
            "    Found existing installation: pydantic_core 2.23.4\n",
            "    Uninstalling pydantic_core-2.23.4:\n",
            "      Successfully uninstalled pydantic_core-2.23.4\n",
            "  Attempting uninstall: Pillow\n",
            "    Found existing installation: pillow 11.0.0\n",
            "    Uninstalling pillow-11.0.0:\n",
            "      Successfully uninstalled pillow-11.0.0\n",
            "  Attempting uninstall: markupsafe\n",
            "    Found existing installation: MarkupSafe 3.0.2\n",
            "    Uninstalling MarkupSafe-3.0.2:\n",
            "      Successfully uninstalled MarkupSafe-3.0.2\n",
            "  Attempting uninstall: llvmlite\n",
            "    Found existing installation: llvmlite 0.43.0\n",
            "    Uninstalling llvmlite-0.43.0:\n",
            "      Successfully uninstalled llvmlite-0.43.0\n",
            "  Attempting uninstall: fsspec\n",
            "    Found existing installation: fsspec 2024.10.0\n",
            "    Uninstalling fsspec-2024.10.0:\n",
            "      Successfully uninstalled fsspec-2024.10.0\n",
            "  Attempting uninstall: pydantic\n",
            "    Found existing installation: pydantic 2.9.2\n",
            "    Uninstalling pydantic-2.9.2:\n",
            "      Successfully uninstalled pydantic-2.9.2\n",
            "  Attempting uninstall: numba\n",
            "    Found existing installation: numba 0.60.0\n",
            "    Uninstalling numba-0.60.0:\n",
            "      Successfully uninstalled numba-0.60.0\n",
            "  Attempting uninstall: accelerate\n",
            "    Found existing installation: accelerate 1.1.1\n",
            "    Uninstalling accelerate-1.1.1:\n",
            "      Successfully uninstalled accelerate-1.1.1\n",
            "  Attempting uninstall: peft\n",
            "    Found existing installation: peft 0.13.2\n",
            "    Uninstalling peft-0.13.2:\n",
            "      Successfully uninstalled peft-0.13.2\n",
            "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
            "gcsfs 2024.10.0 requires fsspec==2024.10.0, but you have fsspec 2024.9.0 which is incompatible.\u001b[0m\u001b[31m\n",
            "\u001b[0mSuccessfully installed Pillow-10.4.0 SpeechRecognition-3.10.0 accelerate-1.0.1 aiofiles-23.2.1 bitsandbytes-0.44.1 colorama-0.4.6 cramjam-2.9.0 datasets-3.1.0 dill-0.3.8 diskcache-5.6.3 exllamav2-0.2.3+cu121.torch2.4.1 fastapi-0.112.4 fastparquet-2024.11.0 ffmpy-0.4.0 flash-attn-2.6.3 flask_cloudflared-0.0.14 fsspec-2024.9.0 gradio-4.26.0 gradio-client-0.15.1 llama-cpp-python-0.3.1+cpuavx2 llama-cpp-python-cuda-0.3.1+cu121 llama-cpp-python-cuda-tensorcores-0.3.1+cu121 llvmlite-0.42.0 markupsafe-2.1.5 multiprocess-0.70.16 ninja-1.11.1.2 numba-0.59.1 peft-0.12.0 pydantic-2.8.2 pydantic-core-2.20.1 pydub-0.25.1 python-multipart-0.0.19 ruff-0.8.1 semantic-version-2.10.0 sse-starlette-1.6.5 starlette-0.38.6 tiktoken-0.8.0 tomlkit-0.12.0 uvicorn-0.32.1 websockets-11.0.3 xxhash-3.5.0\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.colab-display-data+json": {
              "pip_warning": {
                "packages": [
                  "PIL"
                ]
              },
              "id": "c508779f32934f99b8c0524fb52e52ef"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[0m\n",
            "Download Results:\n",
            "gid   |stat|avg speed  |path/URI\n",
            "======+====+===========+=======================================================\n",
            "d3009a|\u001b[1;32mOK\u001b[0m  |   155MiB/s|/content/text-generation-webui/models//INTELLECT-1-Instruct-Q6_K.gguf\n",
            "\n",
            "Status Legend:\n",
            "(OK):download completed.\n",
            "/content/text-generation-webui\n",
            "\u001b[2;36m09:54:00-625354\u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m Starting Text generation web UI                                            \n",
            "\u001b[2;36m09:54:01-043560\u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m Loading \u001b[32m\"INTELLECT-1-Instruct-Q6_K.gguf\"\u001b[0m                                   \n",
            "\u001b[2;36m09:54:01-438231\u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m llama.cpp weights detected: \u001b[32m\"models/INTELLECT-1-Instruct-Q6_K.gguf\"\u001b[0m        \n",
            "llama_model_loader: loaded meta data with 95 key-value pairs and 381 tensors from models/INTELLECT-1-Instruct-Q6_K.gguf (version GGUF V3 (latest))\n",
            "llama_model_loader: Dumping metadata keys/values. Note: KV overrides do not apply in this output.\n",
            "llama_model_loader: - kv   0:                       general.architecture str              = llama\n",
            "llama_model_loader: - kv   1:                               general.type str              = model\n",
            "llama_model_loader: - kv   2:                               general.name str              = INTELLECT 1 Instruct\n",
            "llama_model_loader: - kv   3:                       general.organization str              = PrimeIntellect\n",
            "llama_model_loader: - kv   4:                           general.finetune str              = Instruct\n",
            "llama_model_loader: - kv   5:                           general.basename str              = INTELLECT-1\n",
            "llama_model_loader: - kv   6:                         general.size_label str              = 10B\n",
            "llama_model_loader: - kv   7:                            general.license str              = apache-2.0\n",
            "llama_model_loader: - kv   8:                   general.base_model.count u32              = 1\n",
            "llama_model_loader: - kv   9:                  general.base_model.0.name str              = INTELLECT 1\n",
            "llama_model_loader: - kv  10:               general.base_model.0.version str              = 1\n",
            "llama_model_loader: - kv  11:          general.base_model.0.organization str              = PrimeIntellect\n",
            "llama_model_loader: - kv  12:              general.base_model.0.repo_url str              = https://huggingface.co/PrimeIntellect...\n",
            "llama_model_loader: - kv  13:                      general.dataset.count u32              = 19\n",
            "llama_model_loader: - kv  14:                     general.dataset.0.name str              = Fineweb Edu\n",
            "llama_model_loader: - kv  15:             general.dataset.0.organization str              = PrimeIntellect\n",
            "llama_model_loader: - kv  16:                 general.dataset.0.repo_url str              = https://huggingface.co/PrimeIntellect...\n",
            "llama_model_loader: - kv  17:                     general.dataset.1.name str              = Fineweb\n",
            "llama_model_loader: - kv  18:             general.dataset.1.organization str              = PrimeIntellect\n",
            "llama_model_loader: - kv  19:                 general.dataset.1.repo_url str              = https://huggingface.co/PrimeIntellect...\n",
            "llama_model_loader: - kv  20:                     general.dataset.2.name str              = StackV1 Popular\n",
            "llama_model_loader: - kv  21:             general.dataset.2.organization str              = PrimeIntellect\n",
            "llama_model_loader: - kv  22:                 general.dataset.2.repo_url str              = https://huggingface.co/PrimeIntellect...\n",
            "llama_model_loader: - kv  23:                     general.dataset.3.name str              = Dclm Baseline 1.0 Parquet\n",
            "llama_model_loader: - kv  24:             general.dataset.3.organization str              = Mlfoundations\n",
            "llama_model_loader: - kv  25:                 general.dataset.3.repo_url str              = https://huggingface.co/mlfoundations/...\n",
            "llama_model_loader: - kv  26:                     general.dataset.4.name str              = Open Web Math\n",
            "llama_model_loader: - kv  27:             general.dataset.4.organization str              = Open Web Math\n",
            "llama_model_loader: - kv  28:                 general.dataset.4.repo_url str              = https://huggingface.co/open-web-math/...\n",
            "llama_model_loader: - kv  29:                     general.dataset.5.name str              = EvolKit 75K\n",
            "llama_model_loader: - kv  30:             general.dataset.5.organization str              = Arcee Ai\n",
            "llama_model_loader: - kv  31:                 general.dataset.5.repo_url str              = https://huggingface.co/arcee-ai/EvolK...\n",
            "llama_model_loader: - kv  32:                     general.dataset.6.name str              = Llama 405B Logits\n",
            "llama_model_loader: - kv  33:             general.dataset.6.organization str              = Arcee Ai\n",
            "llama_model_loader: - kv  34:                 general.dataset.6.repo_url str              = https://huggingface.co/arcee-ai/Llama...\n",
            "llama_model_loader: - kv  35:                     general.dataset.7.name str              = The Tomb\n",
            "llama_model_loader: - kv  36:             general.dataset.7.organization str              = Arcee Ai\n",
            "llama_model_loader: - kv  37:                 general.dataset.7.repo_url str              = https://huggingface.co/arcee-ai/The-Tomb\n",
            "llama_model_loader: - kv  38:                     general.dataset.8.name str              = Open Perfectblend Fixed\n",
            "llama_model_loader: - kv  39:             general.dataset.8.organization str              = Mlabonne\n",
            "llama_model_loader: - kv  40:                 general.dataset.8.repo_url str              = https://huggingface.co/mlabonne/open-...\n",
            "llama_model_loader: - kv  41:                     general.dataset.9.name str              = Orca Agentinstruct 1M v1 Cleaned\n",
            "llama_model_loader: - kv  42:                  general.dataset.9.version str              = v1\n",
            "llama_model_loader: - kv  43:             general.dataset.9.organization str              = Microsoft\n",
            "llama_model_loader: - kv  44:                 general.dataset.9.repo_url str              = https://huggingface.co/microsoft/orca...\n",
            "llama_model_loader: - kv  45:                    general.dataset.10.name str              = AutoIF Instruct 61k With Funcs\n",
            "llama_model_loader: - kv  46:            general.dataset.10.organization str              = Post Training Data Flywheel\n",
            "llama_model_loader: - kv  47:                general.dataset.10.repo_url str              = https://huggingface.co/Post-training-...\n",
            "llama_model_loader: - kv  48:                    general.dataset.11.name str              = ToolACE\n",
            "llama_model_loader: - kv  49:            general.dataset.11.organization str              = Team ACE\n",
            "llama_model_loader: - kv  50:                general.dataset.11.repo_url str              = https://huggingface.co/Team-ACE/ToolACE\n",
            "llama_model_loader: - kv  51:                    general.dataset.12.name str              = Synthia Coder\n",
            "llama_model_loader: - kv  52:                    general.dataset.13.name str              = M2Lingual\n",
            "llama_model_loader: - kv  53:            general.dataset.13.organization str              = ServiceNow AI\n",
            "llama_model_loader: - kv  54:                general.dataset.13.repo_url str              = https://huggingface.co/ServiceNow-AI/...\n",
            "llama_model_loader: - kv  55:                    general.dataset.14.name str              = NuminaMath TIR\n",
            "llama_model_loader: - kv  56:            general.dataset.14.organization str              = AI MO\n",
            "llama_model_loader: - kv  57:                general.dataset.14.repo_url str              = https://huggingface.co/AI-MO/NuminaMa...\n",
            "llama_model_loader: - kv  58:                    general.dataset.15.name str              = Tulu 3 Sft Personas Code\n",
            "llama_model_loader: - kv  59:            general.dataset.15.organization str              = Allenai\n",
            "llama_model_loader: - kv  60:                general.dataset.15.repo_url str              = https://huggingface.co/allenai/tulu-3...\n",
            "llama_model_loader: - kv  61:                    general.dataset.16.name str              = Tulu 3 Sft Personas Math\n",
            "llama_model_loader: - kv  62:            general.dataset.16.organization str              = Allenai\n",
            "llama_model_loader: - kv  63:                general.dataset.16.repo_url str              = https://huggingface.co/allenai/tulu-3...\n",
            "llama_model_loader: - kv  64:                    general.dataset.17.name str              = Tulu 3 Sft Personas Math Grade\n",
            "llama_model_loader: - kv  65:            general.dataset.17.organization str              = Allenai\n",
            "llama_model_loader: - kv  66:                general.dataset.17.repo_url str              = https://huggingface.co/allenai/tulu-3...\n",
            "llama_model_loader: - kv  67:                    general.dataset.18.name str              = Tulu 3 Sft Personas Algebra\n",
            "llama_model_loader: - kv  68:            general.dataset.18.organization str              = Allenai\n",
            "llama_model_loader: - kv  69:                general.dataset.18.repo_url str              = https://huggingface.co/allenai/tulu-3...\n",
            "llama_model_loader: - kv  70:                               general.tags arr[str,1]       = [\"text-generation\"]\n",
            "llama_model_loader: - kv  71:                          general.languages arr[str,1]       = [\"en\"]\n",
            "llama_model_loader: - kv  72:                          llama.block_count u32              = 42\n",
            "llama_model_loader: - kv  73:                       llama.context_length u32              = 8192\n",
            "llama_model_loader: - kv  74:                     llama.embedding_length u32              = 4096\n",
            "llama_model_loader: - kv  75:                  llama.feed_forward_length u32              = 14336\n",
            "llama_model_loader: - kv  76:                 llama.attention.head_count u32              = 32\n",
            "llama_model_loader: - kv  77:              llama.attention.head_count_kv u32              = 8\n",
            "llama_model_loader: - kv  78:                       llama.rope.freq_base f32              = 500000.000000\n",
            "llama_model_loader: - kv  79:     llama.attention.layer_norm_rms_epsilon f32              = 0.000010\n",
            "llama_model_loader: - kv  80:                 llama.attention.key_length u32              = 128\n",
            "llama_model_loader: - kv  81:               llama.attention.value_length u32              = 128\n",
            "llama_model_loader: - kv  82:                          general.file_type u32              = 18\n",
            "llama_model_loader: - kv  83:                           llama.vocab_size u32              = 128256\n",
            "llama_model_loader: - kv  84:                 llama.rope.dimension_count u32              = 128\n",
            "llama_model_loader: - kv  85:                       tokenizer.ggml.model str              = gpt2\n",
            "llama_model_loader: - kv  86:                         tokenizer.ggml.pre str              = llama-bpe\n",
            "llama_model_loader: - kv  87:                      tokenizer.ggml.tokens arr[str,128256]  = [\"!\", \"\\\"\", \"#\", \"$\", \"%\", \"&\", \"'\", ...\n",
            "llama_model_loader: - kv  88:                  tokenizer.ggml.token_type arr[i32,128256]  = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...\n",
            "llama_model_loader: - kv  89:                      tokenizer.ggml.merges arr[str,280147]  = [\"Ġ Ġ\", \"Ġ ĠĠĠ\", \"ĠĠ ĠĠ\", \"...\n",
            "llama_model_loader: - kv  90:                tokenizer.ggml.bos_token_id u32              = 128000\n",
            "llama_model_loader: - kv  91:                tokenizer.ggml.eos_token_id u32              = 128009\n",
            "llama_model_loader: - kv  92:            tokenizer.ggml.padding_token_id u32              = 128255\n",
            "llama_model_loader: - kv  93:                    tokenizer.chat_template str              = {% if not add_generation_prompt is de...\n",
            "llama_model_loader: - kv  94:               general.quantization_version u32              = 2\n",
            "llama_model_loader: - type  f32:   85 tensors\n",
            "llama_model_loader: - type q6_K:  296 tensors\n",
            "llm_load_vocab: special tokens cache size = 256\n",
            "llm_load_vocab: token to piece cache size = 0.8000 MB\n",
            "llm_load_print_meta: format           = GGUF V3 (latest)\n",
            "llm_load_print_meta: arch             = llama\n",
            "llm_load_print_meta: vocab type       = BPE\n",
            "llm_load_print_meta: n_vocab          = 128256\n",
            "llm_load_print_meta: n_merges         = 280147\n",
            "llm_load_print_meta: vocab_only       = 0\n",
            "llm_load_print_meta: n_ctx_train      = 8192\n",
            "llm_load_print_meta: n_embd           = 4096\n",
            "llm_load_print_meta: n_layer          = 42\n",
            "llm_load_print_meta: n_head           = 32\n",
            "llm_load_print_meta: n_head_kv        = 8\n",
            "llm_load_print_meta: n_rot            = 128\n",
            "llm_load_print_meta: n_swa            = 0\n",
            "llm_load_print_meta: n_embd_head_k    = 128\n",
            "llm_load_print_meta: n_embd_head_v    = 128\n",
            "llm_load_print_meta: n_gqa            = 4\n",
            "llm_load_print_meta: n_embd_k_gqa     = 1024\n",
            "llm_load_print_meta: n_embd_v_gqa     = 1024\n",
            "llm_load_print_meta: f_norm_eps       = 0.0e+00\n",
            "llm_load_print_meta: f_norm_rms_eps   = 1.0e-05\n",
            "llm_load_print_meta: f_clamp_kqv      = 0.0e+00\n",
            "llm_load_print_meta: f_max_alibi_bias = 0.0e+00\n",
            "llm_load_print_meta: f_logit_scale    = 0.0e+00\n",
            "llm_load_print_meta: n_ff             = 14336\n",
            "llm_load_print_meta: n_expert         = 0\n",
            "llm_load_print_meta: n_expert_used    = 0\n",
            "llm_load_print_meta: causal attn      = 1\n",
            "llm_load_print_meta: pooling type     = 0\n",
            "llm_load_print_meta: rope type        = 0\n",
            "llm_load_print_meta: rope scaling     = linear\n",
            "llm_load_print_meta: freq_base_train  = 500000.0\n",
            "llm_load_print_meta: freq_scale_train = 1\n",
            "llm_load_print_meta: n_ctx_orig_yarn  = 8192\n",
            "llm_load_print_meta: rope_finetuned   = unknown\n",
            "llm_load_print_meta: ssm_d_conv       = 0\n",
            "llm_load_print_meta: ssm_d_inner      = 0\n",
            "llm_load_print_meta: ssm_d_state      = 0\n",
            "llm_load_print_meta: ssm_dt_rank      = 0\n",
            "llm_load_print_meta: ssm_dt_b_c_rms   = 0\n",
            "llm_load_print_meta: model type       = ?B\n",
            "llm_load_print_meta: model ftype      = Q6_K\n",
            "llm_load_print_meta: model params     = 10.21 B\n",
            "llm_load_print_meta: model size       = 7.80 GiB (6.56 BPW) \n",
            "llm_load_print_meta: general.name     = INTELLECT 1 Instruct\n",
            "llm_load_print_meta: BOS token        = 128000 '<|begin_of_text|>'\n",
            "llm_load_print_meta: EOS token        = 128009 '<|eot_id|>'\n",
            "llm_load_print_meta: PAD token        = 128255 '<|reserved_special_token_250|>'\n",
            "llm_load_print_meta: LF token         = 128 'Ä'\n",
            "llm_load_print_meta: EOT token        = 128009 '<|eot_id|>'\n",
            "llm_load_print_meta: EOG token        = 128009 '<|eot_id|>'\n",
            "llm_load_print_meta: max token length = 256\n",
            "ggml_cuda_init: GGML_CUDA_FORCE_MMQ:    yes\n",
            "ggml_cuda_init: GGML_CUDA_FORCE_CUBLAS: no\n",
            "ggml_cuda_init: found 1 CUDA devices:\n",
            "  Device 0: Tesla T4, compute capability 7.5, VMM: yes\n",
            "llm_load_tensors: ggml ctx size =    0.36 MiB\n",
            "llm_load_tensors: offloading 42 repeating layers to GPU\n",
            "llm_load_tensors: offloading non-repeating layers to GPU\n",
            "llm_load_tensors: offloaded 43/43 layers to GPU\n",
            "llm_load_tensors:        CPU buffer size =   410.98 MiB\n",
            "llm_load_tensors:      CUDA0 buffer size =  7578.55 MiB\n",
            "............................................................................................\n",
            "llama_new_context_with_model: n_ctx      = 2048\n",
            "llama_new_context_with_model: n_batch    = 512\n",
            "llama_new_context_with_model: n_ubatch   = 512\n",
            "llama_new_context_with_model: flash_attn = 0\n",
            "llama_new_context_with_model: freq_base  = 500000.0\n",
            "llama_new_context_with_model: freq_scale = 1\n",
            "llama_kv_cache_init:      CUDA0 KV buffer size =   336.00 MiB\n",
            "llama_new_context_with_model: KV self size  =  336.00 MiB, K (f16):  168.00 MiB, V (f16):  168.00 MiB\n",
            "llama_new_context_with_model:  CUDA_Host  output buffer size =     0.49 MiB\n",
            "llama_new_context_with_model:      CUDA0 compute buffer size =   258.50 MiB\n",
            "llama_new_context_with_model:  CUDA_Host compute buffer size =    12.01 MiB\n",
            "llama_new_context_with_model: graph nodes  = 1350\n",
            "llama_new_context_with_model: graph splits = 2\n",
            "AVX = 1 | AVX_VNNI = 0 | AVX2 = 1 | AVX512 = 0 | AVX512_VBMI = 0 | AVX512_VNNI = 0 | AVX512_BF16 = 0 | FMA = 1 | NEON = 0 | SVE = 0 | ARM_FMA = 0 | F16C = 1 | FP16_VA = 0 | RISCV_VECT = 0 | WASM_SIMD = 0 | BLAS = 1 | SSE3 = 1 | SSSE3 = 1 | VSX = 0 | MATMUL_INT8 = 0 | LLAMAFILE = 1 | \n",
            "Model metadata: {'general.quantization_version': '2', 'tokenizer.ggml.eos_token_id': '128009', 'tokenizer.ggml.bos_token_id': '128000', 'tokenizer.ggml.pre': 'llama-bpe', 'tokenizer.ggml.model': 'gpt2', 'llama.rope.dimension_count': '128', 'llama.attention.value_length': '128', 'llama.attention.head_count_kv': '8', 'llama.embedding_length': '4096', 'llama.block_count': '42', 'general.dataset.18.repo_url': 'https://huggingface.co/allenai/tulu-3-sft-personas-algebra', 'general.dataset.18.name': 'Tulu 3 Sft Personas Algebra', 'general.dataset.17.repo_url': 'https://huggingface.co/allenai/tulu-3-sft-personas-math-grade', 'general.dataset.17.organization': 'Allenai', 'general.dataset.17.name': 'Tulu 3 Sft Personas Math Grade', 'general.dataset.16.organization': 'Allenai', 'general.dataset.16.name': 'Tulu 3 Sft Personas Math', 'tokenizer.ggml.padding_token_id': '128255', 'llama.context_length': '8192', 'general.dataset.15.repo_url': 'https://huggingface.co/allenai/tulu-3-sft-personas-code', 'general.dataset.15.organization': 'Allenai', 'llama.rope.freq_base': '500000.000000', 'general.dataset.3.repo_url': 'https://huggingface.co/mlfoundations/dclm-baseline-1.0-parquet', 'general.dataset.18.organization': 'Allenai', 'general.dataset.3.organization': 'Mlfoundations', 'general.finetune': 'Instruct', 'general.dataset.0.organization': 'PrimeIntellect', 'general.dataset.2.organization': 'PrimeIntellect', 'llama.feed_forward_length': '14336', 'general.dataset.2.name': 'StackV1 Popular', 'general.base_model.0.organization': 'PrimeIntellect', 'general.dataset.1.organization': 'PrimeIntellect', 'llama.attention.key_length': '128', 'general.dataset.4.organization': 'Open Web Math', 'general.dataset.7.repo_url': 'https://huggingface.co/arcee-ai/The-Tomb', 'general.dataset.4.name': 'Open Web Math', 'llama.vocab_size': '128256', 'general.dataset.3.name': 'Dclm Baseline 1.0 Parquet', 'general.dataset.9.name': 'Orca Agentinstruct 1M v1 Cleaned', 'general.base_model.0.version': '1', 'general.dataset.2.repo_url': 'https://huggingface.co/PrimeIntellect/StackV1-popular', 'general.architecture': 'llama', 'llama.attention.head_count': '32', 'general.dataset.16.repo_url': 'https://huggingface.co/allenai/tulu-3-sft-personas-math', 'general.name': 'INTELLECT 1 Instruct', 'general.base_model.0.name': 'INTELLECT 1', 'general.dataset.10.name': 'AutoIF Instruct 61k With Funcs', 'general.dataset.0.name': 'Fineweb Edu', 'general.dataset.5.organization': 'Arcee Ai', 'general.organization': 'PrimeIntellect', 'general.dataset.8.organization': 'Mlabonne', 'general.dataset.12.name': 'Synthia Coder', 'general.size_label': '10B', 'general.dataset.4.repo_url': 'https://huggingface.co/open-web-math/open-web-math', 'general.dataset.1.repo_url': 'https://huggingface.co/PrimeIntellect/fineweb', 'general.license': 'apache-2.0', 'general.dataset.0.repo_url': 'https://huggingface.co/PrimeIntellect/fineweb-edu', 'general.dataset.6.organization': 'Arcee Ai', 'general.dataset.1.name': 'Fineweb', 'general.dataset.5.name': 'EvolKit 75K', 'general.dataset.10.organization': 'Post Training Data Flywheel', 'general.dataset.5.repo_url': 'https://huggingface.co/arcee-ai/EvolKit-75K', 'general.dataset.9.organization': 'Microsoft', 'general.type': 'model', 'general.dataset.10.repo_url': 'https://huggingface.co/Post-training-Data-Flywheel/AutoIF-instruct-61k-with-funcs', 'general.dataset.6.repo_url': 'https://huggingface.co/arcee-ai/Llama-405B-Logits', 'general.dataset.6.name': 'Llama 405B Logits', 'general.dataset.7.name': 'The Tomb', 'tokenizer.chat_template': \"{% if not add_generation_prompt is defined %}{% set add_generation_prompt = false %}{% endif %}{% set loop_messages = messages %}{% for message in loop_messages %}{% set content = '<|start_header_id|>' + message['role'] + '<|end_header_id|>\\n\\n'+ message['content'] | trim + '<|eot_id|>' %}{% if loop.index0 == 0 %}{% set content = bos_token + content %}{% endif %}{{ content }}{% endfor %}{% if add_generation_prompt %}{{ '<|start_header_id|>assistant<|end_header_id|>\\n\\n' }}{% endif %}\", 'general.dataset.7.organization': 'Arcee Ai', 'general.basename': 'INTELLECT-1', 'general.dataset.8.name': 'Open Perfectblend Fixed', 'general.file_type': '18', 'general.dataset.8.repo_url': 'https://huggingface.co/mlabonne/open-perfectblend-fixed', 'general.dataset.15.name': 'Tulu 3 Sft Personas Code', 'general.dataset.11.organization': 'Team ACE', 'general.dataset.9.version': 'v1', 'general.dataset.9.repo_url': 'https://huggingface.co/microsoft/orca-agentinstruct-1M-v1-cleaned', 'general.dataset.count': '19', 'general.dataset.11.name': 'ToolACE', 'general.dataset.14.organization': 'AI MO', 'general.dataset.11.repo_url': 'https://huggingface.co/Team-ACE/ToolACE', 'general.dataset.13.name': 'M2Lingual', 'llama.attention.layer_norm_rms_epsilon': '0.000010', 'general.dataset.13.organization': 'ServiceNow AI', 'general.base_model.count': '1', 'general.dataset.13.repo_url': 'https://huggingface.co/ServiceNow-AI/M2Lingual', 'general.base_model.0.repo_url': 'https://huggingface.co/PrimeIntellect/INTELLECT-1', 'general.dataset.14.name': 'NuminaMath TIR', 'general.dataset.14.repo_url': 'https://huggingface.co/AI-MO/NuminaMath-TIR'}\n",
            "Available chat formats from metadata: chat_template.default\n",
            "Using gguf chat template: {% if not add_generation_prompt is defined %}{% set add_generation_prompt = false %}{% endif %}{% set loop_messages = messages %}{% for message in loop_messages %}{% set content = '<|start_header_id|>' + message['role'] + '<|end_header_id|>\n",
            "\n",
            "'+ message['content'] | trim + '<|eot_id|>' %}{% if loop.index0 == 0 %}{% set content = bos_token + content %}{% endif %}{{ content }}{% endfor %}{% if add_generation_prompt %}{{ '<|start_header_id|>assistant<|end_header_id|>\n",
            "\n",
            "' }}{% endif %}\n",
            "Using chat eos_token: <|eot_id|>\n",
            "Using chat bos_token: <|begin_of_text|>\n",
            "\u001b[2;36m09:54:35-398813\u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m Loaded \u001b[32m\"INTELLECT-1-Instruct-Q6_K.gguf\"\u001b[0m in \u001b[1;36m34.35\u001b[0m seconds.                  \n",
            "\u001b[2;36m09:54:35-400116\u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m LOADER: \u001b[32m\"llama.cpp\"\u001b[0m                                                        \n",
            "\u001b[2;36m09:54:35-401075\u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m TRUNCATION LENGTH: \u001b[1;36m2048\u001b[0m                                                    \n",
            "\u001b[2;36m09:54:35-401955\u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m INSTRUCTION TEMPLATE: \u001b[32m\"Custom \u001b[0m\u001b[32m(\u001b[0m\u001b[32mobtained from model metadata\u001b[0m\u001b[32m)\u001b[0m\u001b[32m\"\u001b[0m              \n",
            "\n",
            "Running on local URL:  http://127.0.0.1:7860\n",
            "\n",
            "Running on public URL: https://747a8974fbe19bed37.gradio.live\n",
            "\n",
            "This share link expires in 72 hours. For free permanent hosting and GPU upgrades, run `gradio deploy` from Terminal to deploy to Spaces (https://huggingface.co/spaces)\n",
            "/usr/local/lib/python3.10/dist-packages/llama_cpp_cuda/llama.py:1238: RuntimeWarning: Detected duplicate leading \"<|begin_of_text|>\" in prompt, this will likely reduce response quality, consider removing it...\n",
            "  warnings.warn(\n",
            "llama_perf_context_print:        load time =     515.38 ms\n",
            "llama_perf_context_print: prompt eval time =       0.00 ms /    27 tokens (    0.00 ms per token,      inf tokens per second)\n",
            "llama_perf_context_print:        eval time =       0.00 ms /   187 runs   (    0.00 ms per token,      inf tokens per second)\n",
            "llama_perf_context_print:       total time =   11890.48 ms /   214 tokens\n",
            "Output generated in 12.42 seconds (15.06 tokens/s, 187 tokens, context 58, seed 1123857175)\n",
            "\u001b[2;36m09:56:09-883310\u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m Deleted \u001b[32m\"logs/instruct/20241205-09-55-22.json\"\u001b[0m.                            \n",
            "Llama.generate: 6 prefix-match hit, remaining 24 prompt tokens to eval\n",
            "llama_perf_context_print:        load time =     515.38 ms\n",
            "llama_perf_context_print: prompt eval time =       0.00 ms /    24 tokens (    0.00 ms per token,      inf tokens per second)\n",
            "llama_perf_context_print:        eval time =       0.00 ms /    66 runs   (    0.00 ms per token,      inf tokens per second)\n",
            "llama_perf_context_print:       total time =    4350.05 ms /    90 tokens\n",
            "Output generated in 4.84 seconds (13.64 tokens/s, 66 tokens, context 61, seed 885300060)\n",
            "\u001b[2;36m09:57:14-428183\u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m Deleted \u001b[32m\"logs/instruct/20241205-09-56-09.json\"\u001b[0m.                            \n",
            "Llama.generate: 6 prefix-match hit, remaining 47 prompt tokens to eval\n",
            "llama_perf_context_print:        load time =     515.38 ms\n",
            "llama_perf_context_print: prompt eval time =       0.00 ms /    47 tokens (    0.00 ms per token,      inf tokens per second)\n",
            "llama_perf_context_print:        eval time =       0.00 ms /   693 runs   (    0.00 ms per token,      inf tokens per second)\n",
            "llama_perf_context_print:       total time =   42890.48 ms /   740 tokens\n",
            "Output generated in 43.44 seconds (15.95 tokens/s, 693 tokens, context 84, seed 91113833)\n"
          ]
        }
      ],
      "source": [
        "%cd /content\n",
        "!apt-get -y install -qq aria2\n",
        "!pip install torch==2.2.2 torchvision==0.17.2 torchaudio==2.2.2 --index-url https://download.pytorch.org/whl/cu121\n",
        "\n",
        "!git clone -b V20241028 https://github.com/Troyanovsky/text-generation-webui\n",
        "%cd /content/text-generation-webui\n",
        "!pip install -r requirements.txt\n",
        "\n",
        "!aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lmstudio-community/INTELLECT-1-Instruct-GGUF/resolve/main/INTELLECT-1-Instruct-Q6_K.gguf?download=true -d /content/text-generation-webui/models/ -o INTELLECT-1-Instruct-Q6_K.gguf\n",
        "\n",
        "%cd /content/text-generation-webui\n",
        "!python server.py --share --n-gpu-layers 100000 --model INTELLECT-1-Instruct-Q6_K.gguf --n_ctx 2048"
      ]
    }
  ],
  "metadata": {
    "accelerator": "GPU",
    "colab": {
      "provenance": [],
      "authorship_tag": "ABX9TyOajcf3c8f/ChG8T4/9cVoE",
      "include_colab_link": true
    },
    "gpuClass": "standard",
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}