Llama_3_1_Storm_8B_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/Llama_3_1_Storm_8B_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": [
        "## Llama-3.1-Storm-8B-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. Pick the version you need from one of the last two cells and only run that cell.\n",
        "3. Click the gradio link at the bottom\n",
        "4. In Parameter settings - Instruction Template:\n",
        "\n",
        "```\n",
        "<|begin_of_text|><|start_header_id|>system<|end_header_id|>\n",
        "\n",
        "{system_prompt}<|eot_id|><|start_header_id|>user<|end_header_id|>\n",
        "\n",
        "{prompt}<|eot_id|><|start_header_id|>assistant<|end_header_id|>\n",
        "```\n",
        "\n",
        "Original model: https://huggingface.co/akjindal53244/Llama-3.1-Storm-8B\n",
        "\n",
        "Quantized model: https://huggingface.co/bartowski/Llama-3.1-Storm-8B-GGUF\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": "598fc16e-0aa8-42ec-dc61-367f08e3a1e7"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/content\n",
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            "Processing triggers for man-db (2.10.2-1) ...\n",
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            "/sbin/ldconfig.real: /usr/local/lib/libtbbbind.so.3 is not a symbolic link\n",
            "\n",
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            "/sbin/ldconfig.real: /usr/local/lib/libur_adapter_level_zero.so.0 is not a symbolic link\n",
            "\n",
            "/sbin/ldconfig.real: /usr/local/lib/libur_loader.so.0 is not a symbolic link\n",
            "\n",
            "Cloning into 'text-generation-webui'...\n",
            "remote: Enumerating objects: 18825, done.\u001b[K\n",
            "remote: Counting objects: 100% (459/459), done.\u001b[K\n",
            "remote: Compressing objects: 100% (211/211), done.\u001b[K\n",
            "remote: Total 18825 (delta 319), reused 352 (delta 248), pack-reused 18366 (from 1)\u001b[K\n",
            "Receiving objects: 100% (18825/18825), 27.83 MiB | 15.17 MiB/s, done.\n",
            "Resolving deltas: 100% (13325/13325), done.\n",
            "Note: switching to 'd011040f43c447d699dfd4cf863198907e16c10d'.\n",
            "\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",
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            "Using cached nvidia_nvjitlink_cu12-12.6.20-py3-none-manylinux2014_x86_64.whl (19.7 MB)\n",
            "Building wheels for collected packages: hqq, rouge-score, sqlitedict\n",
            "  Building wheel for hqq (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for hqq: filename=hqq-0.1.7.post3-py3-none-any.whl size=59172 sha256=ca3b3acf68ace128cfa4db852138803ec37003a79a04b619b86847ab2cd297f8\n",
            "  Stored in directory: /root/.cache/pip/wheels/e6/48/52/64097324429cfc0c8e47c763b060a132484cdb0a99483ecf82\n",
            "  Building wheel for rouge-score (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for rouge-score: filename=rouge_score-0.1.2-py3-none-any.whl size=24935 sha256=ba15bf41d3f33f64317bc17b7f3484a53d6e2054f8b2f8b04308316c4e349e98\n",
            "  Stored in directory: /root/.cache/pip/wheels/5f/dd/89/461065a73be61a532ff8599a28e9beef17985c9e9c31e541b4\n",
            "  Building wheel for sqlitedict (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for sqlitedict: filename=sqlitedict-2.1.0-py3-none-any.whl size=16863 sha256=b3130fc950c5bb25f37a98bae9a929f02d5cab24f1d1094e59abc2354f1143b5\n",
            "  Stored in directory: /root/.cache/pip/wheels/79/d6/e7/304e0e6cb2221022c26d8161f7c23cd4f259a9e41e8bbcfabd\n",
            "Successfully built hqq rouge-score sqlitedict\n",
            "Installing collected packages: sqlitedict, pydub, ninja, zstandard, xxhash, websockets, triton, tomlkit, tcolorpy, smmap, setproctitle, sentry-sdk, semantic-version, ruff, rouge, python-multipart, pycountry, pybind11, pyarrow, portalocker, Pillow, pathvalidate, orjson, nvidia-nvtx-cu12, nvidia-nvjitlink-cu12, nvidia-nccl-cu12, nvidia-curand-cu12, nvidia-cufft-cu12, nvidia-cuda-runtime-cu12, nvidia-cuda-nvrtc-cu12, nvidia-cuda-cupti-cu12, nvidia-cublas-cu12, mbstrdecoder, llvmlite, jsonlines, jiter, humanfriendly, h11, gekko, ffmpy, docker-pycreds, diskcache, dill, cramjam, colorama, aiofiles, uvicorn, typepy, tqdm-multiprocess, tiktoken, starlette, SpeechRecognition, sacrebleu, rouge-score, nvidia-cusparse-cu12, nvidia-cudnn-cu12, numba, multiprocess, llama-cpp-python-cuda-tensorcores, llama-cpp-python-cuda, llama-cpp-python, httpcore, gitdb, coloredlogs, sse-starlette, nvidia-cusolver-cu12, httpx, gitpython, flask_cloudflared, fastparquet, fastapi, wandb, transformers, torch, openai, gradio-client, exllamav2, datasets, DataProperty, tabledata, gradio, flash-attn, bitsandbytes, autoawq-kernels, pytablewriter, peft, optimum, hqq, autoawq, aqlm, lm_eval, auto-gptq\n",
            "  Attempting uninstall: triton\n",
            "    Found existing installation: triton 2.3.1\n",
            "    Uninstalling triton-2.3.1:\n",
            "      Successfully uninstalled triton-2.3.1\n",
            "  Attempting uninstall: tomlkit\n",
            "    Found existing installation: tomlkit 0.13.2\n",
            "    Uninstalling tomlkit-0.13.2:\n",
            "      Successfully uninstalled tomlkit-0.13.2\n",
            "  Attempting uninstall: pyarrow\n",
            "    Found existing installation: pyarrow 14.0.2\n",
            "    Uninstalling pyarrow-14.0.2:\n",
            "      Successfully uninstalled pyarrow-14.0.2\n",
            "  Attempting uninstall: Pillow\n",
            "    Found existing installation: Pillow 9.4.0\n",
            "    Uninstalling Pillow-9.4.0:\n",
            "      Successfully uninstalled Pillow-9.4.0\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: 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: transformers\n",
            "    Found existing installation: transformers 4.42.4\n",
            "    Uninstalling transformers-4.42.4:\n",
            "      Successfully uninstalled transformers-4.42.4\n",
            "  Attempting uninstall: torch\n",
            "    Found existing installation: torch 2.3.1+cu121\n",
            "    Uninstalling torch-2.3.1+cu121:\n",
            "      Successfully uninstalled torch-2.3.1+cu121\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",
            "cudf-cu12 24.4.1 requires pyarrow<15.0.0a0,>=14.0.1, but you have pyarrow 17.0.0 which is incompatible.\n",
            "ibis-framework 8.0.0 requires pyarrow<16,>=2, but you have pyarrow 17.0.0 which is incompatible.\n",
            "torchaudio 2.3.1+cu121 requires torch==2.3.1, but you have torch 2.2.2 which is incompatible.\n",
            "torchtext 0.18.0 requires torch>=2.3.0, but you have torch 2.2.2 which is incompatible.\n",
            "torchvision 0.18.1+cu121 requires torch==2.3.1, but you have torch 2.2.2 which is incompatible.\u001b[0m\u001b[31m\n",
            "\u001b[0mSuccessfully installed DataProperty-1.0.1 Pillow-10.4.0 SpeechRecognition-3.10.0 aiofiles-23.2.1 aqlm-1.1.6 auto-gptq-0.7.1 autoawq-0.2.6 autoawq-kernels-0.0.7 bitsandbytes-0.43.3 colorama-0.4.6 coloredlogs-15.0.1 cramjam-2.8.3 datasets-2.21.0 dill-0.3.8 diskcache-5.6.3 docker-pycreds-0.4.0 exllamav2-0.1.8+cu121.torch2.2.2 fastapi-0.112.1 fastparquet-2024.5.0 ffmpy-0.4.0 flash-attn-2.6.1 flask_cloudflared-0.0.14 gekko-1.2.1 gitdb-4.0.11 gitpython-3.1.43 gradio-4.26.0 gradio-client-0.15.1 h11-0.14.0 hqq-0.1.7.post3 httpcore-1.0.5 httpx-0.27.0 humanfriendly-10.0 jiter-0.5.0 jsonlines-4.0.0 llama-cpp-python-0.2.85+cpuavx2 llama-cpp-python-cuda-0.2.85+cu121 llama-cpp-python-cuda-tensorcores-0.2.85+cu121 llvmlite-0.42.0 lm_eval-0.3.0 mbstrdecoder-1.1.3 multiprocess-0.70.16 ninja-1.11.1.1 numba-0.59.1 nvidia-cublas-cu12-12.1.3.1 nvidia-cuda-cupti-cu12-12.1.105 nvidia-cuda-nvrtc-cu12-12.1.105 nvidia-cuda-runtime-cu12-12.1.105 nvidia-cudnn-cu12-8.9.2.26 nvidia-cufft-cu12-11.0.2.54 nvidia-curand-cu12-10.3.2.106 nvidia-cusolver-cu12-11.4.5.107 nvidia-cusparse-cu12-12.1.0.106 nvidia-nccl-cu12-2.19.3 nvidia-nvjitlink-cu12-12.6.20 nvidia-nvtx-cu12-12.1.105 openai-1.41.1 optimum-1.17.1 orjson-3.10.7 pathvalidate-3.2.0 peft-0.8.2 portalocker-2.10.1 pyarrow-17.0.0 pybind11-2.13.4 pycountry-24.6.1 pydub-0.25.1 pytablewriter-1.2.0 python-multipart-0.0.9 rouge-1.0.1 rouge-score-0.1.2 ruff-0.6.1 sacrebleu-1.5.0 semantic-version-2.10.0 sentry-sdk-2.13.0 setproctitle-1.3.3 smmap-5.0.1 sqlitedict-2.1.0 sse-starlette-1.6.5 starlette-0.38.2 tabledata-1.3.3 tcolorpy-0.1.6 tiktoken-0.7.0 tomlkit-0.12.0 torch-2.2.2 tqdm-multiprocess-0.0.11 transformers-4.43.4 triton-2.2.0 typepy-1.3.2 uvicorn-0.30.6 wandb-0.17.7 websockets-11.0.3 xxhash-3.5.0 zstandard-0.23.0\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.colab-display-data+json": {
              "pip_warning": {
                "packages": [
                  "PIL"
                ]
              },
              "id": "b30b25302d5f4babb65ba24c87c08147"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
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            "\u001b[33mWARNING: typer 0.12.3 does not provide the extra 'all'\u001b[0m\u001b[33m\n",
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            "\u001b[0m\n",
            "Download Results:\n",
            "gid   |stat|avg speed  |path/URI\n",
            "======+====+===========+=======================================================\n",
            "d7a1fa|\u001b[1;32mOK\u001b[0m  |   190MiB/s|/content/text-generation-webui/models//Llama-3.1-Storm-8B-Q5_K_M.gguf\n",
            "\n",
            "Status Legend:\n",
            "(OK):download completed.\n",
            "/content/text-generation-webui\n",
            "\u001b[2;36m02:33:27-273597\u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m Starting Text generation web UI                                            \n",
            "\u001b[2;36m02:33:28-012342\u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m Loading \u001b[32m\"Llama-3.1-Storm-8B-Q5_K_M.gguf\"\u001b[0m                                   \n",
            "\u001b[2;36m02:33:28-627788\u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m llama.cpp weights detected: \u001b[32m\"models/Llama-3.1-Storm-8B-Q5_K_M.gguf\"\u001b[0m        \n",
            "llama_model_loader: loaded meta data with 34 key-value pairs and 292 tensors from models/Llama-3.1-Storm-8B-Q5_K_M.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              = Llama 3.1 Storm 8B\n",
            "llama_model_loader: - kv   3:                       general.organization str              = Akjindal53244\n",
            "llama_model_loader: - kv   4:                           general.basename str              = Llama-3.1-Storm\n",
            "llama_model_loader: - kv   5:                         general.size_label str              = 8B\n",
            "llama_model_loader: - kv   6:                            general.license str              = llama3.1\n",
            "llama_model_loader: - kv   7:                               general.tags arr[str,9]       = [\"llama-3.1\", \"conversational\", \"inst...\n",
            "llama_model_loader: - kv   8:                          general.languages arr[str,8]       = [\"en\", \"de\", \"fr\", \"it\", \"pt\", \"hi\", ...\n",
            "llama_model_loader: - kv   9:                          llama.block_count u32              = 32\n",
            "llama_model_loader: - kv  10:                       llama.context_length u32              = 131072\n",
            "llama_model_loader: - kv  11:                     llama.embedding_length u32              = 4096\n",
            "llama_model_loader: - kv  12:                  llama.feed_forward_length u32              = 14336\n",
            "llama_model_loader: - kv  13:                 llama.attention.head_count u32              = 32\n",
            "llama_model_loader: - kv  14:              llama.attention.head_count_kv u32              = 8\n",
            "llama_model_loader: - kv  15:                       llama.rope.freq_base f32              = 500000.000000\n",
            "llama_model_loader: - kv  16:     llama.attention.layer_norm_rms_epsilon f32              = 0.000010\n",
            "llama_model_loader: - kv  17:                          general.file_type u32              = 17\n",
            "llama_model_loader: - kv  18:                           llama.vocab_size u32              = 128256\n",
            "llama_model_loader: - kv  19:                 llama.rope.dimension_count u32              = 128\n",
            "llama_model_loader: - kv  20:                       tokenizer.ggml.model str              = gpt2\n",
            "llama_model_loader: - kv  21:                         tokenizer.ggml.pre str              = llama-bpe\n",
            "llama_model_loader: - kv  22:                      tokenizer.ggml.tokens arr[str,128256]  = [\"!\", \"\\\"\", \"#\", \"$\", \"%\", \"&\", \"'\", ...\n",
            "llama_model_loader: - kv  23:                  tokenizer.ggml.token_type arr[i32,128256]  = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...\n",
            "llama_model_loader: - kv  24:                      tokenizer.ggml.merges arr[str,280147]  = [\"Ġ Ġ\", \"Ġ ĠĠĠ\", \"ĠĠ ĠĠ\", \"...\n",
            "llama_model_loader: - kv  25:                tokenizer.ggml.bos_token_id u32              = 128000\n",
            "llama_model_loader: - kv  26:                tokenizer.ggml.eos_token_id u32              = 128009\n",
            "llama_model_loader: - kv  27:            tokenizer.ggml.padding_token_id u32              = 128001\n",
            "llama_model_loader: - kv  28:                    tokenizer.chat_template str              = {% set loop_messages = messages %}{% ...\n",
            "llama_model_loader: - kv  29:               general.quantization_version u32              = 2\n",
            "llama_model_loader: - kv  30:                      quantize.imatrix.file str              = /models_out/Llama-3.1-Storm-8B-GGUF/L...\n",
            "llama_model_loader: - kv  31:                   quantize.imatrix.dataset str              = /training_dir/calibration_datav3.txt\n",
            "llama_model_loader: - kv  32:             quantize.imatrix.entries_count i32              = 224\n",
            "llama_model_loader: - kv  33:              quantize.imatrix.chunks_count i32              = 125\n",
            "llama_model_loader: - type  f32:   66 tensors\n",
            "llama_model_loader: - type q5_K:  193 tensors\n",
            "llama_model_loader: - type q6_K:   33 tensors\n",
            "llm_load_vocab: special tokens cache size = 256\n",
            "llm_load_vocab: token to piece cache size = 0.7999 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      = 131072\n",
            "llm_load_print_meta: n_embd           = 4096\n",
            "llm_load_print_meta: n_layer          = 32\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  = 131072\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: model type       = 8B\n",
            "llm_load_print_meta: model ftype      = Q5_K - Medium\n",
            "llm_load_print_meta: model params     = 8.03 B\n",
            "llm_load_print_meta: model size       = 5.33 GiB (5.70 BPW) \n",
            "llm_load_print_meta: general.name     = Llama 3.1 Storm 8B\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        = 128001 '<|end_of_text|>'\n",
            "llm_load_print_meta: LF token         = 128 'Ä'\n",
            "llm_load_print_meta: EOT 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 =    0.27 MiB\n",
            "llm_load_tensors: offloading 32 repeating layers to GPU\n",
            "llm_load_tensors: offloading non-repeating layers to GPU\n",
            "llm_load_tensors: offloaded 33/33 layers to GPU\n",
            "llm_load_tensors:        CPU buffer size =   344.44 MiB\n",
            "llm_load_tensors:      CUDA0 buffer size =  5115.50 MiB\n",
            ".........................................................................................\n",
            "llama_new_context_with_model: n_ctx      = 8224\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 =  1028.00 MiB\n",
            "llama_new_context_with_model: KV self size  = 1028.00 MiB, K (f16):  514.00 MiB, V (f16):  514.00 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 =   562.07 MiB\n",
            "llama_new_context_with_model:  CUDA_Host compute buffer size =    24.07 MiB\n",
            "llama_new_context_with_model: graph nodes  = 1030\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 | WASM_SIMD = 0 | BLAS = 1 | SSE3 = 1 | SSSE3 = 1 | VSX = 0 | MATMUL_INT8 = 0 | LLAMAFILE = 1 | \n",
            "Model metadata: {'quantize.imatrix.entries_count': '224', 'quantize.imatrix.dataset': '/training_dir/calibration_datav3.txt', 'quantize.imatrix.chunks_count': '125', 'quantize.imatrix.file': '/models_out/Llama-3.1-Storm-8B-GGUF/Llama-3.1-Storm-8B.imatrix', 'tokenizer.chat_template': \"{% 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 %}{{ '<|start_header_id|>assistant<|end_header_id|>\\n\\n' }}\", 'tokenizer.ggml.eos_token_id': '128009', 'general.quantization_version': '2', 'tokenizer.ggml.model': 'gpt2', 'llama.rope.dimension_count': '128', 'llama.vocab_size': '128256', 'general.file_type': '17', 'llama.attention.layer_norm_rms_epsilon': '0.000010', 'llama.rope.freq_base': '500000.000000', 'general.architecture': 'llama', 'tokenizer.ggml.padding_token_id': '128001', 'general.basename': 'Llama-3.1-Storm', 'tokenizer.ggml.bos_token_id': '128000', 'llama.attention.head_count': '32', 'tokenizer.ggml.pre': 'llama-bpe', 'llama.context_length': '131072', 'general.name': 'Llama 3.1 Storm 8B', 'general.organization': 'Akjindal53244', 'general.type': 'model', 'general.size_label': '8B', 'general.license': 'llama3.1', 'llama.feed_forward_length': '14336', 'llama.embedding_length': '4096', 'llama.block_count': '32', 'llama.attention.head_count_kv': '8'}\n",
            "Available chat formats from metadata: chat_template.default\n",
            "Using gguf chat template: {% 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 %}{{ '<|start_header_id|>assistant<|end_header_id|>\n",
            "\n",
            "' }}\n",
            "Using chat eos_token: <|eot_id|>\n",
            "Using chat bos_token: <|begin_of_text|>\n",
            "\u001b[2;36m02:33:49-674267\u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m Loaded \u001b[32m\"Llama-3.1-Storm-8B-Q5_K_M.gguf\"\u001b[0m in \u001b[1;36m21.66\u001b[0m seconds.                  \n",
            "\u001b[2;36m02:33:49-675725\u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m LOADER: \u001b[32m\"llama.cpp\"\u001b[0m                                                        \n",
            "\u001b[2;36m02:33:49-676683\u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m TRUNCATION LENGTH: \u001b[1;36m8196\u001b[0m                                                    \n",
            "\u001b[2;36m02:33:49-677580\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://86cab3cfb3de67099d.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:1129: RuntimeWarning: Detected duplicate leading \"<|begin_of_text|>\" in prompt, this will likely reduce response quality, consider removing it...\n",
            "  warnings.warn(\n",
            "\n",
            "llama_print_timings:        load time =     524.57 ms\n",
            "llama_print_timings:      sample time =    1715.85 ms /   182 runs   (    9.43 ms per token,   106.07 tokens per second)\n",
            "llama_print_timings: prompt eval time =     523.57 ms /    27 tokens (   19.39 ms per token,    51.57 tokens per second)\n",
            "llama_print_timings:        eval time =    5030.53 ms /   181 runs   (   27.79 ms per token,    35.98 tokens per second)\n",
            "llama_print_timings:       total time =   10256.94 ms /   208 tokens\n",
            "Output generated in 10.98 seconds (16.49 tokens/s, 181 tokens, context 58, seed 468570503)\n",
            "Llama.generate: prefix-match hit\n",
            "\n",
            "llama_print_timings:        load time =     524.57 ms\n",
            "llama_print_timings:      sample time =     642.20 ms /    72 runs   (    8.92 ms per token,   112.12 tokens per second)\n",
            "llama_print_timings: prompt eval time =      93.89 ms /    27 tokens (    3.48 ms per token,   287.56 tokens per second)\n",
            "llama_print_timings:        eval time =    1973.23 ms /    71 runs   (   27.79 ms per token,    35.98 tokens per second)\n",
            "llama_print_timings:       total time =    3925.54 ms /    98 tokens\n",
            "Output generated in 4.80 seconds (14.80 tokens/s, 71 tokens, context 297, seed 471948143)\n",
            "\u001b[2;36m02:39:15-356215\u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m Deleted \u001b[32m\"logs/instruct/20240820-02-38-05.json\"\u001b[0m.                            \n",
            "Llama.generate: prefix-match hit\n",
            "\n",
            "llama_print_timings:        load time =     524.57 ms\n",
            "llama_print_timings:      sample time =     157.73 ms /    19 runs   (    8.30 ms per token,   120.46 tokens per second)\n",
            "llama_print_timings: prompt eval time =      92.70 ms /    28 tokens (    3.31 ms per token,   302.05 tokens per second)\n",
            "llama_print_timings:        eval time =     525.85 ms /    18 runs   (   29.21 ms per token,    34.23 tokens per second)\n",
            "llama_print_timings:       total time =    1030.30 ms /    46 tokens\n",
            "Output generated in 1.73 seconds (10.43 tokens/s, 18 tokens, context 65, seed 913135877)\n"
          ]
        }
      ],
      "source": [
        "%cd /content\n",
        "!apt-get -y install -qq aria2\n",
        "\n",
        "!git clone -b V20240819 https://github.com/Troyanovsky/text-generation-webui\n",
        "%cd /content/text-generation-webui\n",
        "!pip install -r requirements.txt\n",
        "!pip install -U gradio==4.26.0\n",
        "\n",
        "!aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/bartowski/Llama-3.1-Storm-8B-GGUF/resolve/main/Llama-3.1-Storm-8B-Q5_K_M.gguf?download=true -d /content/text-generation-webui/models/ -o Llama-3.1-Storm-8B-Q5_K_M.gguf\n",
        "\n",
        "%cd /content/text-generation-webui\n",
        "!python server.py --share --n-gpu-layers 100000 --model Llama-3.1-Storm-8B-Q5_K_M.gguf --n_ctx 8196"
      ]
    }
  ],
  "metadata": {
    "accelerator": "GPU",
    "colab": {
      "provenance": [],
      "authorship_tag": "ABX9TyOPCtME+Xg9uoi8GvtjHZ7Y",
      "include_colab_link": true
    },
    "gpuClass": "standard",
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}