Gemma_2_9B_It_SPPO_Iter3_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/Gemma_2_9B_It_SPPO_Iter3_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": [
        "## Gemma-2-9B-It-SPPO-Iter3-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",
        "<bos><start_of_turn>user\n",
        "{prompt}<end_of_turn>\n",
        "<start_of_turn>model\n",
        "<end_of_turn>\n",
        "<start_of_turn>model\n",
        "```\n",
        "\n",
        "Original model: https://huggingface.co/UCLA-AGI/Gemma-2-9B-It-SPPO-Iter3\n",
        "\n",
        "Quantized model: https://huggingface.co/bartowski/Gemma-2-9B-It-SPPO-Iter3-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": "843cc53c-f61a-47da-ffb6-ec28a42b2794"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/content\n",
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            "\n",
            "Cloning into 'text-generation-webui'...\n",
            "remote: Enumerating objects: 18825, done.\u001b[K\n",
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            "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=c27447fcd879abae8734601920e469097b22ef0e57f35e345cbd72f74b9874ad\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=352c92256d30410db5a2ab9f04e71ae100570b2450061e10fc2084becec28b0e\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=b18c2ac83da17e687f098179a93a7edb33fc3fae5274f0be2d66fd2fbdd7b9a4\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 0.13.0\n",
            "    Uninstalling tomlkit-0.13.0:\n",
            "      Successfully uninstalled tomlkit-0.13.0\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-1.41.0 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": "c38784427f0f4f2882bc562c0c10b553"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
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            " *** Download Progress Summary as of Mon Aug 19 06:52:53 2024 *** \n",
            "=\n",
            "[#4f2af7 5.8GiB/6.1GiB(94%) CN:16 DL:36MiB ETA:10s]\n",
            "FILE: /content/text-generation-webui/models//Gemma-2-9B-It-SPPO-Iter3-Q5_K_M.gguf\n",
            "-\n",
            "\n",
            "\u001b[0m\n",
            "Download Results:\n",
            "gid   |stat|avg speed  |path/URI\n",
            "======+====+===========+=======================================================\n",
            "4f2af7|\u001b[1;32mOK\u001b[0m  |    89MiB/s|/content/text-generation-webui/models//Gemma-2-9B-It-SPPO-Iter3-Q5_K_M.gguf\n",
            "\n",
            "Status Legend:\n",
            "(OK):download completed.\n",
            "/content/text-generation-webui\n",
            "\u001b[2;36m06:53:12-397679\u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m Starting Text generation web UI                                            \n",
            "\u001b[2;36m06:53:12-963764\u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m Loading \u001b[32m\"Gemma-2-9B-It-SPPO-Iter3-Q5_K_M.gguf\"\u001b[0m                             \n",
            "\u001b[2;36m06:53:13-543055\u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m llama.cpp weights detected: \u001b[32m\"models/Gemma-2-9B-It-SPPO-Iter3-Q5_K_M.gguf\"\u001b[0m  \n",
            "llama_model_loader: loaded meta data with 33 key-value pairs and 464 tensors from models/Gemma-2-9B-It-SPPO-Iter3-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              = gemma2\n",
            "llama_model_loader: - kv   1:                               general.name str              = Gemma-2-9B-It-SPPO-Iter3\n",
            "llama_model_loader: - kv   2:                      gemma2.context_length u32              = 8192\n",
            "llama_model_loader: - kv   3:                    gemma2.embedding_length u32              = 3584\n",
            "llama_model_loader: - kv   4:                         gemma2.block_count u32              = 42\n",
            "llama_model_loader: - kv   5:                 gemma2.feed_forward_length u32              = 14336\n",
            "llama_model_loader: - kv   6:                gemma2.attention.head_count u32              = 16\n",
            "llama_model_loader: - kv   7:             gemma2.attention.head_count_kv u32              = 8\n",
            "llama_model_loader: - kv   8:    gemma2.attention.layer_norm_rms_epsilon f32              = 0.000001\n",
            "llama_model_loader: - kv   9:                gemma2.attention.key_length u32              = 256\n",
            "llama_model_loader: - kv  10:              gemma2.attention.value_length u32              = 256\n",
            "llama_model_loader: - kv  11:                          general.file_type u32              = 17\n",
            "llama_model_loader: - kv  12:              gemma2.attn_logit_softcapping f32              = 50.000000\n",
            "llama_model_loader: - kv  13:             gemma2.final_logit_softcapping f32              = 30.000000\n",
            "llama_model_loader: - kv  14:            gemma2.attention.sliding_window u32              = 4096\n",
            "llama_model_loader: - kv  15:                       tokenizer.ggml.model str              = llama\n",
            "llama_model_loader: - kv  16:                         tokenizer.ggml.pre str              = default\n",
            "llama_model_loader: - kv  17:                      tokenizer.ggml.tokens arr[str,256000]  = [\"<pad>\", \"<eos>\", \"<bos>\", \"<unk>\", ...\n",
            "llama_model_loader: - kv  18:                      tokenizer.ggml.scores arr[f32,256000]  = [-1000.000000, -1000.000000, -1000.00...\n",
            "llama_model_loader: - kv  19:                  tokenizer.ggml.token_type arr[i32,256000]  = [3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, ...\n",
            "llama_model_loader: - kv  20:                tokenizer.ggml.bos_token_id u32              = 2\n",
            "llama_model_loader: - kv  21:                tokenizer.ggml.eos_token_id u32              = 1\n",
            "llama_model_loader: - kv  22:            tokenizer.ggml.unknown_token_id u32              = 3\n",
            "llama_model_loader: - kv  23:            tokenizer.ggml.padding_token_id u32              = 0\n",
            "llama_model_loader: - kv  24:               tokenizer.ggml.add_bos_token bool             = true\n",
            "llama_model_loader: - kv  25:               tokenizer.ggml.add_eos_token bool             = false\n",
            "llama_model_loader: - kv  26:                    tokenizer.chat_template str              = {{ bos_token }}{% if messages[0]['rol...\n",
            "llama_model_loader: - kv  27:            tokenizer.ggml.add_space_prefix bool             = false\n",
            "llama_model_loader: - kv  28:               general.quantization_version u32              = 2\n",
            "llama_model_loader: - kv  29:                      quantize.imatrix.file str              = /models_out/Gemma-2-9B-It-SPPO-Iter3-...\n",
            "llama_model_loader: - kv  30:                   quantize.imatrix.dataset str              = /training_dir/calibration_datav3.txt\n",
            "llama_model_loader: - kv  31:             quantize.imatrix.entries_count i32              = 294\n",
            "llama_model_loader: - kv  32:              quantize.imatrix.chunks_count i32              = 128\n",
            "llama_model_loader: - type  f32:  169 tensors\n",
            "llama_model_loader: - type q5_K:  252 tensors\n",
            "llama_model_loader: - type q6_K:   43 tensors\n",
            "llm_load_vocab: special tokens cache size = 217\n",
            "llm_load_vocab: token to piece cache size = 1.6014 MB\n",
            "llm_load_print_meta: format           = GGUF V3 (latest)\n",
            "llm_load_print_meta: arch             = gemma2\n",
            "llm_load_print_meta: vocab type       = SPM\n",
            "llm_load_print_meta: n_vocab          = 256000\n",
            "llm_load_print_meta: n_merges         = 0\n",
            "llm_load_print_meta: vocab_only       = 0\n",
            "llm_load_print_meta: n_ctx_train      = 8192\n",
            "llm_load_print_meta: n_embd           = 3584\n",
            "llm_load_print_meta: n_layer          = 42\n",
            "llm_load_print_meta: n_head           = 16\n",
            "llm_load_print_meta: n_head_kv        = 8\n",
            "llm_load_print_meta: n_rot            = 256\n",
            "llm_load_print_meta: n_swa            = 4096\n",
            "llm_load_print_meta: n_embd_head_k    = 256\n",
            "llm_load_print_meta: n_embd_head_v    = 256\n",
            "llm_load_print_meta: n_gqa            = 2\n",
            "llm_load_print_meta: n_embd_k_gqa     = 2048\n",
            "llm_load_print_meta: n_embd_v_gqa     = 2048\n",
            "llm_load_print_meta: f_norm_eps       = 0.0e+00\n",
            "llm_load_print_meta: f_norm_rms_eps   = 1.0e-06\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        = 2\n",
            "llm_load_print_meta: rope scaling     = linear\n",
            "llm_load_print_meta: freq_base_train  = 10000.0\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: model type       = 9B\n",
            "llm_load_print_meta: model ftype      = Q5_K - Medium\n",
            "llm_load_print_meta: model params     = 9.24 B\n",
            "llm_load_print_meta: model size       = 6.19 GiB (5.75 BPW) \n",
            "llm_load_print_meta: general.name     = Gemma-2-9B-It-SPPO-Iter3\n",
            "llm_load_print_meta: BOS token        = 2 '<bos>'\n",
            "llm_load_print_meta: EOS token        = 1 '<eos>'\n",
            "llm_load_print_meta: UNK token        = 3 '<unk>'\n",
            "llm_load_print_meta: PAD token        = 0 '<pad>'\n",
            "llm_load_print_meta: LF token         = 227 '<0x0A>'\n",
            "llm_load_print_meta: EOT token        = 107 '<end_of_turn>'\n",
            "llm_load_print_meta: max token length = 48\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 =    0.41 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 =   717.77 MiB\n",
            "llm_load_tensors:      CUDA0 buffer size =  6333.65 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  = 10000.0\n",
            "llama_new_context_with_model: freq_scale = 1\n",
            "llama_kv_cache_init:      CUDA0 KV buffer size =  2698.50 MiB\n",
            "llama_new_context_with_model: KV self size  = 2698.50 MiB, K (f16): 1349.25 MiB, V (f16): 1349.25 MiB\n",
            "llama_new_context_with_model:  CUDA_Host  output buffer size =     0.98 MiB\n",
            "llama_new_context_with_model:      CUDA0 compute buffer size =   507.00 MiB\n",
            "llama_new_context_with_model:  CUDA_Host compute buffer size =    39.13 MiB\n",
            "llama_new_context_with_model: graph nodes  = 1690\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.chunks_count': '128', 'gemma2.attn_logit_softcapping': '50.000000', 'gemma2.attention.value_length': '256', 'gemma2.attention.sliding_window': '4096', 'gemma2.attention.head_count': '16', 'gemma2.feed_forward_length': '14336', 'gemma2.block_count': '42', 'tokenizer.ggml.pre': 'default', 'gemma2.embedding_length': '3584', 'general.file_type': '17', 'gemma2.attention.layer_norm_rms_epsilon': '0.000001', 'gemma2.context_length': '8192', 'tokenizer.chat_template': \"{{ bos_token }}{% if messages[0]['role'] == 'system' %}{{ raise_exception('System role not supported') }}{% endif %}{% for message in messages %}{% if (message['role'] == 'user') != (loop.index0 % 2 == 0) %}{{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...') }}{% endif %}{% if (message['role'] == 'assistant') %}{% set role = 'model' %}{% else %}{% set role = message['role'] %}{% endif %}{{ '<start_of_turn>' + role + '\\n' + message['content'] | trim + '<end_of_turn>\\n' }}{% endfor %}{% if add_generation_prompt %}{{'<start_of_turn>model\\n'}}{% endif %}\", 'general.architecture': 'gemma2', 'gemma2.final_logit_softcapping': '30.000000', 'gemma2.attention.head_count_kv': '8', 'tokenizer.ggml.add_eos_token': 'false', 'quantize.imatrix.file': '/models_out/Gemma-2-9B-It-SPPO-Iter3-GGUF/Gemma-2-9B-It-SPPO-Iter3.imatrix', 'tokenizer.ggml.add_space_prefix': 'false', 'tokenizer.ggml.model': 'llama', 'general.quantization_version': '2', 'general.name': 'Gemma-2-9B-It-SPPO-Iter3', 'tokenizer.ggml.bos_token_id': '2', 'tokenizer.ggml.eos_token_id': '1', 'tokenizer.ggml.unknown_token_id': '3', 'tokenizer.ggml.padding_token_id': '0', 'tokenizer.ggml.add_bos_token': 'true', 'gemma2.attention.key_length': '256', 'quantize.imatrix.dataset': '/training_dir/calibration_datav3.txt', 'quantize.imatrix.entries_count': '294'}\n",
            "Available chat formats from metadata: chat_template.default\n",
            "Using gguf chat template: {{ bos_token }}{% if messages[0]['role'] == 'system' %}{{ raise_exception('System role not supported') }}{% endif %}{% for message in messages %}{% if (message['role'] == 'user') != (loop.index0 % 2 == 0) %}{{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...') }}{% endif %}{% if (message['role'] == 'assistant') %}{% set role = 'model' %}{% else %}{% set role = message['role'] %}{% endif %}{{ '<start_of_turn>' + role + '\n",
            "' + message['content'] | trim + '<end_of_turn>\n",
            "' }}{% endfor %}{% if add_generation_prompt %}{{'<start_of_turn>model\n",
            "'}}{% endif %}\n",
            "Using chat eos_token: <eos>\n",
            "Using chat bos_token: <bos>\n",
            "\u001b[2;36m06:53:37-668096\u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m Loaded \u001b[32m\"Gemma-2-9B-It-SPPO-Iter3-Q5_K_M.gguf\"\u001b[0m in \u001b[1;36m24.70\u001b[0m seconds.            \n",
            "\u001b[2;36m06:53:37-669424\u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m LOADER: \u001b[32m\"llama.cpp\"\u001b[0m                                                        \n",
            "\u001b[2;36m06:53:37-670385\u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m TRUNCATION LENGTH: \u001b[1;36m8196\u001b[0m                                                    \n",
            "\u001b[2;36m06:53:37-671281\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://086f0100696604d955.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",
            "\u001b[2;36m07:01:44-636988\u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m Loading \u001b[32m\"Gemma-2-9B-It-SPPO-Iter3-Q5_K_M.gguf\"\u001b[0m                             \n",
            "\u001b[2;36m07:01:45-165562\u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m llama.cpp weights detected: \u001b[32m\"models/Gemma-2-9B-It-SPPO-Iter3-Q5_K_M.gguf\"\u001b[0m  \n",
            "llama_model_loader: loaded meta data with 33 key-value pairs and 464 tensors from models/Gemma-2-9B-It-SPPO-Iter3-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              = gemma2\n",
            "llama_model_loader: - kv   1:                               general.name str              = Gemma-2-9B-It-SPPO-Iter3\n",
            "llama_model_loader: - kv   2:                      gemma2.context_length u32              = 8192\n",
            "llama_model_loader: - kv   3:                    gemma2.embedding_length u32              = 3584\n",
            "llama_model_loader: - kv   4:                         gemma2.block_count u32              = 42\n",
            "llama_model_loader: - kv   5:                 gemma2.feed_forward_length u32              = 14336\n",
            "llama_model_loader: - kv   6:                gemma2.attention.head_count u32              = 16\n",
            "llama_model_loader: - kv   7:             gemma2.attention.head_count_kv u32              = 8\n",
            "llama_model_loader: - kv   8:    gemma2.attention.layer_norm_rms_epsilon f32              = 0.000001\n",
            "llama_model_loader: - kv   9:                gemma2.attention.key_length u32              = 256\n",
            "llama_model_loader: - kv  10:              gemma2.attention.value_length u32              = 256\n",
            "llama_model_loader: - kv  11:                          general.file_type u32              = 17\n",
            "llama_model_loader: - kv  12:              gemma2.attn_logit_softcapping f32              = 50.000000\n",
            "llama_model_loader: - kv  13:             gemma2.final_logit_softcapping f32              = 30.000000\n",
            "llama_model_loader: - kv  14:            gemma2.attention.sliding_window u32              = 4096\n",
            "llama_model_loader: - kv  15:                       tokenizer.ggml.model str              = llama\n",
            "llama_model_loader: - kv  16:                         tokenizer.ggml.pre str              = default\n",
            "llama_model_loader: - kv  17:                      tokenizer.ggml.tokens arr[str,256000]  = [\"<pad>\", \"<eos>\", \"<bos>\", \"<unk>\", ...\n",
            "llama_model_loader: - kv  18:                      tokenizer.ggml.scores arr[f32,256000]  = [-1000.000000, -1000.000000, -1000.00...\n",
            "llama_model_loader: - kv  19:                  tokenizer.ggml.token_type arr[i32,256000]  = [3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, ...\n",
            "llama_model_loader: - kv  20:                tokenizer.ggml.bos_token_id u32              = 2\n",
            "llama_model_loader: - kv  21:                tokenizer.ggml.eos_token_id u32              = 1\n",
            "llama_model_loader: - kv  22:            tokenizer.ggml.unknown_token_id u32              = 3\n",
            "llama_model_loader: - kv  23:            tokenizer.ggml.padding_token_id u32              = 0\n",
            "llama_model_loader: - kv  24:               tokenizer.ggml.add_bos_token bool             = true\n",
            "llama_model_loader: - kv  25:               tokenizer.ggml.add_eos_token bool             = false\n",
            "llama_model_loader: - kv  26:                    tokenizer.chat_template str              = {{ bos_token }}{% if messages[0]['rol...\n",
            "llama_model_loader: - kv  27:            tokenizer.ggml.add_space_prefix bool             = false\n",
            "llama_model_loader: - kv  28:               general.quantization_version u32              = 2\n",
            "llama_model_loader: - kv  29:                      quantize.imatrix.file str              = /models_out/Gemma-2-9B-It-SPPO-Iter3-...\n",
            "llama_model_loader: - kv  30:                   quantize.imatrix.dataset str              = /training_dir/calibration_datav3.txt\n",
            "llama_model_loader: - kv  31:             quantize.imatrix.entries_count i32              = 294\n",
            "llama_model_loader: - kv  32:              quantize.imatrix.chunks_count i32              = 128\n",
            "llama_model_loader: - type  f32:  169 tensors\n",
            "llama_model_loader: - type q5_K:  252 tensors\n",
            "llama_model_loader: - type q6_K:   43 tensors\n",
            "llm_load_vocab: special tokens cache size = 217\n",
            "llm_load_vocab: token to piece cache size = 1.6014 MB\n",
            "llm_load_print_meta: format           = GGUF V3 (latest)\n",
            "llm_load_print_meta: arch             = gemma2\n",
            "llm_load_print_meta: vocab type       = SPM\n",
            "llm_load_print_meta: n_vocab          = 256000\n",
            "llm_load_print_meta: n_merges         = 0\n",
            "llm_load_print_meta: vocab_only       = 0\n",
            "llm_load_print_meta: n_ctx_train      = 8192\n",
            "llm_load_print_meta: n_embd           = 3584\n",
            "llm_load_print_meta: n_layer          = 42\n",
            "llm_load_print_meta: n_head           = 16\n",
            "llm_load_print_meta: n_head_kv        = 8\n",
            "llm_load_print_meta: n_rot            = 256\n",
            "llm_load_print_meta: n_swa            = 4096\n",
            "llm_load_print_meta: n_embd_head_k    = 256\n",
            "llm_load_print_meta: n_embd_head_v    = 256\n",
            "llm_load_print_meta: n_gqa            = 2\n",
            "llm_load_print_meta: n_embd_k_gqa     = 2048\n",
            "llm_load_print_meta: n_embd_v_gqa     = 2048\n",
            "llm_load_print_meta: f_norm_eps       = 0.0e+00\n",
            "llm_load_print_meta: f_norm_rms_eps   = 1.0e-06\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        = 2\n",
            "llm_load_print_meta: rope scaling     = linear\n",
            "llm_load_print_meta: freq_base_train  = 10000.0\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: model type       = 9B\n",
            "llm_load_print_meta: model ftype      = Q5_K - Medium\n",
            "llm_load_print_meta: model params     = 9.24 B\n",
            "llm_load_print_meta: model size       = 6.19 GiB (5.75 BPW) \n",
            "llm_load_print_meta: general.name     = Gemma-2-9B-It-SPPO-Iter3\n",
            "llm_load_print_meta: BOS token        = 2 '<bos>'\n",
            "llm_load_print_meta: EOS token        = 1 '<eos>'\n",
            "llm_load_print_meta: UNK token        = 3 '<unk>'\n",
            "llm_load_print_meta: PAD token        = 0 '<pad>'\n",
            "llm_load_print_meta: LF token         = 227 '<0x0A>'\n",
            "llm_load_print_meta: EOT token        = 107 '<end_of_turn>'\n",
            "llm_load_print_meta: max token length = 48\n",
            "llm_load_tensors: ggml ctx size =    0.41 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 =   717.77 MiB\n",
            "llm_load_tensors:      CUDA0 buffer size =  6333.65 MiB\n",
            "..................................................................................\n",
            "llama_new_context_with_model: n_ctx      = 16416\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  = 10000.0\n",
            "llama_new_context_with_model: freq_scale = 1\n",
            "llama_kv_cache_init:      CUDA0 KV buffer size =  5386.50 MiB\n",
            "llama_new_context_with_model: KV self size  = 5386.50 MiB, K (f16): 2693.25 MiB, V (f16): 2693.25 MiB\n",
            "llama_new_context_with_model:  CUDA_Host  output buffer size =     0.98 MiB\n",
            "llama_new_context_with_model:      CUDA0 compute buffer size =   607.13 MiB\n",
            "llama_new_context_with_model:  CUDA_Host compute buffer size =    71.13 MiB\n",
            "llama_new_context_with_model: graph nodes  = 1690\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.chunks_count': '128', 'gemma2.attn_logit_softcapping': '50.000000', 'gemma2.attention.value_length': '256', 'gemma2.attention.sliding_window': '4096', 'gemma2.attention.head_count': '16', 'gemma2.feed_forward_length': '14336', 'gemma2.block_count': '42', 'tokenizer.ggml.pre': 'default', 'gemma2.embedding_length': '3584', 'general.file_type': '17', 'gemma2.attention.layer_norm_rms_epsilon': '0.000001', 'gemma2.context_length': '8192', 'tokenizer.chat_template': \"{{ bos_token }}{% if messages[0]['role'] == 'system' %}{{ raise_exception('System role not supported') }}{% endif %}{% for message in messages %}{% if (message['role'] == 'user') != (loop.index0 % 2 == 0) %}{{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...') }}{% endif %}{% if (message['role'] == 'assistant') %}{% set role = 'model' %}{% else %}{% set role = message['role'] %}{% endif %}{{ '<start_of_turn>' + role + '\\n' + message['content'] | trim + '<end_of_turn>\\n' }}{% endfor %}{% if add_generation_prompt %}{{'<start_of_turn>model\\n'}}{% endif %}\", 'general.architecture': 'gemma2', 'gemma2.final_logit_softcapping': '30.000000', 'gemma2.attention.head_count_kv': '8', 'tokenizer.ggml.add_eos_token': 'false', 'quantize.imatrix.file': '/models_out/Gemma-2-9B-It-SPPO-Iter3-GGUF/Gemma-2-9B-It-SPPO-Iter3.imatrix', 'tokenizer.ggml.add_space_prefix': 'false', 'tokenizer.ggml.model': 'llama', 'general.quantization_version': '2', 'general.name': 'Gemma-2-9B-It-SPPO-Iter3', 'tokenizer.ggml.bos_token_id': '2', 'tokenizer.ggml.eos_token_id': '1', 'tokenizer.ggml.unknown_token_id': '3', 'tokenizer.ggml.padding_token_id': '0', 'tokenizer.ggml.add_bos_token': 'true', 'gemma2.attention.key_length': '256', 'quantize.imatrix.dataset': '/training_dir/calibration_datav3.txt', 'quantize.imatrix.entries_count': '294'}\n",
            "Available chat formats from metadata: chat_template.default\n",
            "Using gguf chat template: {{ bos_token }}{% if messages[0]['role'] == 'system' %}{{ raise_exception('System role not supported') }}{% endif %}{% for message in messages %}{% if (message['role'] == 'user') != (loop.index0 % 2 == 0) %}{{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...') }}{% endif %}{% if (message['role'] == 'assistant') %}{% set role = 'model' %}{% else %}{% set role = message['role'] %}{% endif %}{{ '<start_of_turn>' + role + '\n",
            "' + message['content'] | trim + '<end_of_turn>\n",
            "' }}{% endfor %}{% if add_generation_prompt %}{{'<start_of_turn>model\n",
            "'}}{% endif %}\n",
            "Using chat eos_token: <eos>\n",
            "Using chat bos_token: <bos>\n",
            "\u001b[2;36m07:01:48-111080\u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m Loaded \u001b[32m\"Gemma-2-9B-It-SPPO-Iter3-Q5_K_M.gguf\"\u001b[0m in \u001b[1;36m3.47\u001b[0m seconds.             \n",
            "\u001b[2;36m07:01:48-112776\u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m LOADER: \u001b[32m\"llama.cpp\"\u001b[0m                                                        \n",
            "\u001b[2;36m07:01:48-113836\u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m TRUNCATION LENGTH: \u001b[1;36m16392\u001b[0m                                                   \n",
            "\u001b[2;36m07:01:48-114837\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",
            "/usr/local/lib/python3.10/dist-packages/llama_cpp_cuda/llama.py:1129: RuntimeWarning: Detected duplicate leading \"<bos>\" in prompt, this will likely reduce response quality, consider removing it...\n",
            "  warnings.warn(\n",
            "\n",
            "llama_print_timings:        load time =    1213.53 ms\n",
            "llama_print_timings:      sample time =   16194.58 ms /   447 runs   (   36.23 ms per token,    27.60 tokens per second)\n",
            "llama_print_timings: prompt eval time =    8039.83 ms /  4639 tokens (    1.73 ms per token,   577.00 tokens per second)\n",
            "llama_print_timings:        eval time =   21400.31 ms /   446 runs   (   47.98 ms per token,    20.84 tokens per second)\n",
            "llama_print_timings:       total time =   59826.22 ms /  5085 tokens\n",
            "Output generated in 60.52 seconds (7.37 tokens/s, 446 tokens, context 4658, seed 1546403963)\n",
            "Traceback (most recent call last):\n",
            "  File \"/usr/local/lib/python3.10/dist-packages/gradio/queueing.py\", line 566, in process_events\n",
            "    response = await route_utils.call_process_api(\n",
            "  File \"/usr/local/lib/python3.10/dist-packages/gradio/route_utils.py\", line 261, in call_process_api\n",
            "    output = await app.get_blocks().process_api(\n",
            "  File \"/usr/local/lib/python3.10/dist-packages/gradio/blocks.py\", line 1786, in process_api\n",
            "    result = await self.call_function(\n",
            "  File \"/usr/local/lib/python3.10/dist-packages/gradio/blocks.py\", line 1350, in call_function\n",
            "    prediction = await utils.async_iteration(iterator)\n",
            "  File \"/usr/local/lib/python3.10/dist-packages/gradio/utils.py\", line 583, in async_iteration\n",
            "    return await iterator.__anext__()\n",
            "  File \"/usr/local/lib/python3.10/dist-packages/gradio/utils.py\", line 576, in __anext__\n",
            "    return await anyio.to_thread.run_sync(\n",
            "  File \"/usr/local/lib/python3.10/dist-packages/anyio/to_thread.py\", line 33, in run_sync\n",
            "    return await get_asynclib().run_sync_in_worker_thread(\n",
            "  File \"/usr/local/lib/python3.10/dist-packages/anyio/_backends/_asyncio.py\", line 877, in run_sync_in_worker_thread\n",
            "    return await future\n",
            "  File \"/usr/local/lib/python3.10/dist-packages/anyio/_backends/_asyncio.py\", line 807, in run\n",
            "    result = context.run(func, *args)\n",
            "  File \"/usr/local/lib/python3.10/dist-packages/gradio/utils.py\", line 559, in run_sync_iterator_async\n",
            "    return next(iterator)\n",
            "  File \"/usr/local/lib/python3.10/dist-packages/gradio/utils.py\", line 742, in gen_wrapper\n",
            "    response = next(iterator)\n",
            "  File \"/content/text-generation-webui/modules/chat.py\", line 436, in generate_chat_reply_wrapper\n",
            "    for i, history in enumerate(generate_chat_reply(text, state, regenerate, _continue, loading_message=True, for_ui=True)):\n",
            "  File \"/content/text-generation-webui/modules/chat.py\", line 403, in generate_chat_reply\n",
            "    for history in chatbot_wrapper(text, state, regenerate=regenerate, _continue=_continue, loading_message=loading_message, for_ui=for_ui):\n",
            "  File \"/content/text-generation-webui/modules/chat.py\", line 348, in chatbot_wrapper\n",
            "    prompt = generate_chat_prompt(text, state, **kwargs)\n",
            "  File \"/content/text-generation-webui/modules/chat.py\", line 195, in generate_chat_prompt\n",
            "    prompt = make_prompt(messages)\n",
            "  File \"/content/text-generation-webui/modules/chat.py\", line 151, in make_prompt\n",
            "    prompt = renderer(messages=messages)\n",
            "  File \"/usr/local/lib/python3.10/dist-packages/jinja2/environment.py\", line 1304, in render\n",
            "    self.environment.handle_exception()\n",
            "  File \"/usr/local/lib/python3.10/dist-packages/jinja2/environment.py\", line 939, in handle_exception\n",
            "    raise rewrite_traceback_stack(source=source)\n",
            "  File \"<template>\", line 1, in top-level template code\n",
            "  File \"/usr/local/lib/python3.10/dist-packages/jinja2/sandbox.py\", line 304, in getitem\n",
            "    return obj[argument]\n",
            "jinja2.exceptions.UndefinedError: list object has no element 0\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/Gemma-2-9B-It-SPPO-Iter3-GGUF/resolve/main/Gemma-2-9B-It-SPPO-Iter3-Q5_K_M.gguf?download=true -d /content/text-generation-webui/models/ -o Gemma-2-9B-It-SPPO-Iter3-Q5_K_M.gguf\n",
        "\n",
        "%cd /content/text-generation-webui\n",
        "!python server.py --share --n-gpu-layers 100000 --model Gemma-2-9B-It-SPPO-Iter3-Q5_K_M.gguf --n_ctx 8196"
      ]
    }
  ],
  "metadata": {
    "accelerator": "GPU",
    "colab": {
      "provenance": [],
      "authorship_tag": "ABX9TyOPsR/zSqMDl/nlM/JkosyJ",
      "include_colab_link": true
    },
    "gpuClass": "standard",
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}